Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose permissions needed, whether this is a mutating operation, rate limits, or what happens on success/failure. 'Add' implies creation, but specifics are missing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple tool name and gets straight to the point without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what a 'collection' is, the implications of different operation types, or what the tool returns. Given the complexity hinted by the enum and nested data object, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are documented in the schema. The description adds no additional meaning beyond implying 'apiId' and 'operationType' are involved. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Add a collection to an API' states the basic action but is vague about what a 'collection' entails in this context. It distinguishes from siblings like 'create_collection' by specifying the target is an API, but lacks specificity about the collection's nature or purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'create_collection' or 'fork_collection'. The description implies it's for adding collections to APIs, but doesn't clarify prerequisites, constraints, or typical use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Add' implies a write/mutation operation, the description doesn't disclose important behavioral traits like required permissions, whether this creates permanent resources, potential side effects, error conditions, or what happens on success/failure. This is inadequate for a tool that presumably modifies system state.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence with zero wasted words. It's appropriately sized for what it communicates and front-loads the essential action and target without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with 6 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what 'Private API Network' means contextually, what happens after addition, whether there are constraints on what can be added, or how this differs from similar creation tools in the sibling list. The combination of mutation behavior and lack of structured metadata requires more descriptive context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the schema already documents all 6 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. The baseline score of 3 reflects that the schema does the heavy lifting for parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Add') and target ('element or folder to Private API Network'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'add_api_collection' or 'create_collection_folder', which appear to perform similar creation operations in related contexts.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools for creating/adding API-related elements (e.g., 'add_api_collection', 'create_collection_folder', 'create_api'), there's no indication of when this specific 'Private API Network' tool is appropriate versus those other creation tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states 'Create a new API', implying a write operation, but doesn't disclose behavioral traits like required permissions, whether it's idempotent, what happens on conflicts (e.g., duplicate names), or the response format. This leaves significant gaps for an agent to understand the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for a basic tool, though it could benefit from more detail given the lack of annotations and output schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a creation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what an API entails in this system, the expected return values, or error conditions. With many sibling tools, more context is needed to guide proper usage and integration.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters (name, summary, description, workspaceId) with descriptions. The tool description adds no additional meaning beyond the schema, such as examples or constraints (e.g., name uniqueness). Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Create a new API' states the action and resource, which is clear but vague. It doesn't specify what constitutes an API in this context or differentiate from sibling tools like 'create_api_version' or 'create_api_schema', leaving ambiguity about the scope of what's being created.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools (e.g., 'create_api_version', 'create_api_schema'), the description lacks context about prerequisites, such as whether an API must exist first for other tools, or when this is the appropriate starting point.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions the character limit ('max 10,000 characters'), which is useful behavioral context. However, it lacks critical details: it doesn't specify permissions required, whether the comment is public/private, if it triggers notifications, or what the response looks like (e.g., success/failure, comment ID). For a mutation tool with zero annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that states the core purpose and key constraint (character limit) with zero wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a mutation with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It covers the basic action and a constraint but misses critical context: permissions, response format, error conditions, and how 'threadId' affects behavior. This leaves significant gaps for an agent to use the tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters ('apiId', 'content', 'threadId') with basic descriptions. The description adds the character limit for 'content', which provides extra semantic value beyond the schema. However, it doesn't explain parameter interactions (e.g., 'threadId' for replies vs. new threads) or format details, keeping it at the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create a new comment') and target resource ('on an API'), which is specific and unambiguous. However, it doesn't distinguish this tool from sibling tools like 'update_api_comment' or 'delete_api_comment' beyond the basic verb difference, nor does it mention the 'threadId' parameter for replies, which is a key functional distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing API), exclusions, or comparisons to sibling tools like 'update_api_comment' or 'delete_api_comment'. The agent must infer usage solely from the tool name and parameters.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'create' which implies a write/mutation operation, but doesn't disclose any behavioral traits: no information about permissions needed, whether this is idempotent, what happens on conflict, rate limits, or what the response looks like. For a creation tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a tool with clear parameters documented in the schema. Every word earns its place by conveying the essential purpose without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a creation tool with 3 required parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what constitutes a successful creation, what format the response takes, error conditions, or how this tool integrates with the broader API lifecycle. The description should provide more context about the operation's outcome and behavioral expectations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents all three parameters (apiId, type, files) with their types, enums, and descriptions. The description adds no additional parameter information beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('create') and resource ('schema for an API'), making the purpose immediately understandable. It distinguishes from siblings like 'create_api' (creates the API itself) and 'create_update_schema_file' (updates schema files), though it doesn't explicitly mention these distinctions. The description is specific but could be more precise about what a 'schema' entails in this context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing API ID), when not to use it, or how it relates to siblings like 'create_api_schema' vs 'create_update_schema_file' or 'sync_collection_with_schema'. The agent must infer usage from the tool name and parameters alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. 'Create' implies a write/mutation operation, but the description doesn't address permissions required, whether this is a destructive operation (e.g., if it affects existing versions), rate limits, or what happens on success/failure. For a creation tool with zero annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with zero wasted words. It's perfectly front-loaded, immediately conveying the core purpose without unnecessary elaboration. Every word earns its place in this minimal but complete statement of function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a creation tool with 6 parameters (4 required), no annotations, and no output schema, the description is inadequate. It doesn't explain what an 'API version' entails in this system, what happens after creation, or provide any context about the creation process. The agent must rely entirely on parameter names and sibling tool inference, which is insufficient for confident tool selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no parameter information beyond what's already in the schema (which has 100% coverage). It doesn't explain relationships between parameters (e.g., how 'schemas' and 'collections' relate to the new version), provide examples, or clarify edge cases. With complete schema documentation, the baseline is 3, but the description fails to add meaningful semantic context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create') and resource ('new version of an API'), making the purpose immediately understandable. It distinguishes from sibling tools like 'create_api' (which creates an API itself) and 'update_api_version' (which modifies an existing version). However, it doesn't specify what constitutes an 'API version' in this context, leaving some ambiguity about the exact nature of the created resource.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing API), when not to use it, or how it differs from similar operations like 'fork_collection' or 'update_api_version'. The agent must infer usage solely from the tool name and parameter requirements.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool creates a new collection, implying a write operation, but does not mention permissions required, whether the operation is idempotent, error handling, or what happens if the workspace ID is invalid. This lack of detail is a significant gap for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. It avoids unnecessary words, though it could be slightly more structured by separating format details into a second sentence for clarity. Overall, it is appropriately concise for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that this is a mutation tool with no annotations and no output schema, the description is incomplete. It lacks details on behavioral aspects like authentication needs, error responses, or the structure of the created collection. For a tool that creates resources in a workspace, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the input schema fully documents the parameters. The description adds minimal value by implying the collection must be in Postman Collection v2.1.0 format, which aligns with the schema's description of 'collection details in Postman Collection Format v2.1'. No additional parameter semantics are provided beyond what the schema already covers.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create a new collection') and the resource ('in a workspace'), and specifies the supported format ('Postman Collection v2.1.0 format'). However, it does not explicitly differentiate this tool from sibling tools like 'create_collection_folder' or 'create_collection_request', which might create similar collections in different contexts or with different structures.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, such as 'create_collection_folder' for nested structures or 'fork_collection' for duplicating existing ones. It mentions workspace context but does not specify prerequisites, exclusions, or typical use cases, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states 'Create' which implies a write/mutation operation, but doesn't address permissions required, whether the operation is idempotent, error conditions, or what happens on success (e.g., returns folder ID). For a creation tool with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that states the core functionality without unnecessary words. It's appropriately sized for a simple creation tool and front-loads the essential information. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a mutation tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what happens after creation (e.g., returns folder object/ID), error handling, or system behavior. For a tool that modifies state, more contextual information is needed to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters (collection_id and folder with name/description). The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain format expectations, constraints, or relationships between parameters. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create') and resource ('new folder in a collection'), making the purpose immediately understandable. It distinguishes from siblings like 'create_collection' (which creates entire collections) and 'update_collection_folder' (which modifies existing folders). However, it doesn't specify what type of collection (e.g., API collection) or folder context, which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing collection), exclusions, or comparisons to similar tools like 'add_pan_element' or 'create_collection_request'. The agent must infer usage from the name and context alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states the action without disclosing behavioral traits. It doesn't mention whether this is a write operation (implied by 'Create'), what permissions are required, how errors are handled, or what happens if the collection_id doesn't exist. For a mutation tool with zero annotation coverage, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a mutation tool (creating requests) with no annotations and no output schema, the description is incomplete. It doesn't explain what a 'request' entails in this context (e.g., HTTP request for API testing), what the tool returns, or error conditions, leaving significant gaps for an AI agent to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters (collection_id, folder_id, request with name, method, url). The description adds no additional meaning about these parameters beyond what's in the schema, such as format examples or constraints, meeting the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create') and target ('new request in a collection'), making the purpose understandable. It distinguishes from siblings like 'create_collection' (which creates collections) and 'create_collection_folder' (which creates folders), though it doesn't explicitly mention these distinctions in the text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'update_collection_request' or 'create_collection_response'. It doesn't mention prerequisites, such as needing an existing collection, or contextual factors like whether this is for API testing or documentation purposes.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states the tool creates something but doesn't disclose permissions required, whether it's idempotent, what happens on failure, or the format of the created response. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every word earns its place, achieving optimal conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what a 'response' is in this API context, what the tool returns, error conditions, or dependencies. Given the complexity implied by nested objects and sibling tools like 'update_collection_response', more context is needed for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents the three required parameters (collection_id, request_id, response). The description adds no additional parameter semantics beyond what's in the schema, such as explaining the relationship between collection and request or what the response object represents. Baseline 3 is appropriate when the schema does all the work.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create') and resource ('new response in a collection'), making the purpose immediately understandable. It distinguishes from siblings like 'create_collection' or 'create_collection_request' by specifying it's for responses. However, it doesn't specify what a 'response' entails in this context, keeping it from a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'update_collection_response' or 'get_collection_response'. The description lacks context about prerequisites (e.g., needing an existing collection and request) or typical use cases, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. While it correctly identifies this as a creation operation, it lacks critical behavioral details: it doesn't mention authentication requirements, permission levels needed, whether the operation is idempotent, what happens on duplicate names, rate limits, or what the response contains. For a mutation tool with zero annotation coverage, this represents significant gaps in behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is exceptionally concise with just two sentences that communicate the essential information: what the tool does and the default workspace behavior. It's front-loaded with the primary purpose and contains no redundant or unnecessary information. Every word earns its place in this efficiently structured description.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool that creates environments with nested objects (environment variables), the description is insufficiently complete. With no annotations, no output schema, and complex nested parameter structures, the description should provide more context about what constitutes a valid environment, how environment variables work, error conditions, or response format. The current description leaves too many operational questions unanswered for proper agent usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, so the schema already fully documents both parameters (environment object with name/values and optional workspace ID). The description adds minimal value beyond the schema by mentioning the default workspace behavior, but doesn't provide additional context about parameter relationships, constraints, or usage patterns. This meets the baseline expectation when schema coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create a new environment') and resource ('in a workspace'), making the purpose immediately understandable. It distinguishes this tool from sibling tools like 'fork_environment' or 'update_environment' by specifying it's for creation rather than duplication or modification. However, it doesn't explicitly differentiate from 'create_collection' or other creation tools beyond the resource type.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides some usage context by explaining the default workspace behavior ('Creates in "My Workspace" if workspace not specified'), which helps guide when to include the optional workspace parameter. However, it doesn't offer explicit guidance on when to use this tool versus alternatives like 'fork_environment' for duplicating existing environments or mention prerequisites such as required permissions. The context is implied rather than comprehensive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. 'Create or update' implies a mutation operation, but it doesn't disclose behavioral traits like whether this requires specific permissions, if it overwrites existing files, what happens on conflicts, or any rate limits. For a mutation tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste—it directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (5 parameters including a nested object, no output schema, and no annotations), the description is incomplete. It doesn't address what the tool returns, error conditions, or how it interacts with sibling tools like 'delete_schema_file'. For a mutation tool with multiple parameters and no structured support, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 80%, which is high, so the baseline is 3 even though the description adds no parameter information. The description doesn't explain what parameters like 'apiId', 'schemaId', or 'root.enabled' mean beyond what's in the schema, but with good schema coverage, this is adequate though not helpful.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Create or update a schema file' clearly states the action (create/update) and resource (schema file), which is better than a tautology. However, it doesn't distinguish this tool from sibling tools like 'create_api_schema' or 'delete_schema_file'—it's vague about what makes this specific schema file operation different from those other schema-related operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools like 'create_api_schema', 'delete_schema_file', and 'get_schema_file_contents', there's no indication of when this create/update operation is appropriate versus those other schema operations, nor any mention of prerequisites or constraints.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the webhook 'triggers collection with custom payload,' implying an event-driven action, but fails to describe critical behaviors: whether this operation is idempotent, what permissions are required, how errors are handled, or what the response looks like. For a creation tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence: 'Creates webhook that triggers collection with custom payload.' It is front-loaded with the core action and outcome, with no redundant words or unnecessary elaboration. Every part of the sentence contributes directly to understanding the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of creating a webhook with nested parameters and no output schema or annotations, the description is insufficiently complete. It lacks details on required inputs beyond what the schema provides, does not explain the 'custom payload' concept, and omits behavioral aspects like error handling or response format. For a tool with this level of complexity, more contextual information is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50%, with parameters like 'workspace' and 'webhook' partially documented in the schema. The description adds minimal value beyond the schema by implying that the webhook triggers a collection, which relates to the 'collection' parameter. However, it does not explain the semantics of 'custom payload' or provide details on the 'events' array, leaving some parameters inadequately clarified.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Creates webhook that triggers collection with custom payload.' It specifies the verb ('creates'), resource ('webhook'), and outcome ('triggers collection with custom payload'), making the purpose unambiguous. However, it does not explicitly differentiate from sibling tools like 'create_collection' or 'create_api', which also create resources but different types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as needing an existing collection or workspace, or specify scenarios where webhooks are appropriate compared to other notification methods. Without such context, users must infer usage from the purpose alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. 'Delete an API' implies a destructive, irreversible mutation, but the description doesn't mention permission requirements, whether deletion is permanent, what happens to dependent resources, or confirmation requirements. This is a significant gap for a destructive operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at just three words, front-loading the essential information with zero wasted words. It follows the principle that every sentence should earn its place - in this case, the single phrase does exactly that.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive deletion tool with no annotations and no output schema, the description is insufficiently complete. It doesn't address critical context like what 'deleting an API' entails (entire removal vs archival), whether there are dependencies or cascading effects, what permissions are required, or what the response looks like. The combination of destructive nature and lack of structured metadata demands more descriptive context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the single parameter 'apiId' clearly documented in the schema. The description adds no additional parameter information beyond what's already in the structured schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Delete an API' clearly states the action (delete) and resource (API), which is better than a tautology. However, it doesn't distinguish this tool from other deletion tools like 'delete_api_comment' or 'delete_api_version' - it's vague about what specific API entity is being deleted versus those alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With multiple deletion tools available (delete_api_comment, delete_api_version, delete_collection_access_key, etc.), there's no indication whether this deletes the entire API versus parts of it, or what prerequisites might be required before deletion.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure but offers nothing beyond the basic action. It doesn't mention whether deletion is permanent/reversible, what permissions are required, whether it affects related data, what happens on success/failure, or any rate limits. For a destructive operation with zero annotation coverage, this is critically inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's appropriately sized for a simple deletion operation and front-loads the essential information. Every word earns its place in conveying the core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive operation with no annotations and no output schema, the description is insufficiently complete. It doesn't address critical behavioral aspects like permanence, permissions, or error conditions. While the schema covers parameters well, the description fails to provide necessary context for safe and appropriate use of this mutation tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with both parameters (apiId and commentId) clearly documented in the schema. The description adds no additional parameter information beyond what the schema already provides. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Delete') and target resource ('an API comment'), providing specific verb+resource combination. It distinguishes this as a deletion operation among siblings that include create_api_comment and update_api_comment, though it doesn't explicitly differentiate from other delete operations like delete_api or delete_api_version.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (e.g., needing specific permissions), when deletion is appropriate versus updating, or how this differs from other deletion tools like delete_api or delete_api_version. The agent must infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Delete' implies a destructive, irreversible action, but the description doesn't specify permissions required, whether deletion is permanent, or any side effects (e.g., impact on related resources). This is a significant gap for a mutation tool with zero annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste—'Delete an API version'—making it front-loaded and easy to parse. Every word earns its place by conveying the core action and target without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive tool with no annotations and no output schema, the description is incomplete. It lacks critical context like behavioral traits (e.g., permanence, permissions), usage guidelines, and output expectations. Given the complexity of deletion operations, this minimal description leaves the agent under-informed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with both parameters ('apiId' and 'versionId') clearly documented in the input schema. The description doesn't add any meaning beyond what the schema provides, such as explaining parameter relationships or constraints. Baseline 3 is appropriate when the schema handles parameter documentation effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Delete') and resource ('an API version'), providing a specific verb+resource combination. However, it doesn't differentiate this tool from other deletion tools like 'delete_api' or 'delete_api_comment' among the siblings, which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, such as 'delete_api' for deleting entire APIs or other deletion tools in the sibling list. There's no mention of prerequisites, consequences, or contextual usage, leaving the agent without operational direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states 'Delete' which implies a destructive mutation, but doesn't disclose whether this is irreversible, requires specific permissions, has side effects, or what happens on success/failure. For a destructive tool with zero annotation coverage, this is a significant gap in behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that states exactly what the tool does with zero wasted words. It's appropriately sized for a simple deletion operation and is immediately understandable without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what 'collection access key' means in this context, what happens after deletion, error conditions, or return values. The agent lacks critical context needed to use this tool safely and effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the single parameter 'keyId' fully documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema ('The collection access key ID to delete'). This meets the baseline of 3 when schema coverage is high.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Delete') and resource ('a collection access key'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'delete_api' or 'delete_environment', but the specificity of 'collection access key' provides adequate clarity for what this tool does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. There's no mention of prerequisites (e.g., needing the key ID from 'list_collection_access_keys'), consequences of deletion, or when not to use it. The agent must infer usage from context alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. 'Delete' implies a destructive mutation, but the description doesn't disclose critical behavioral traits: whether deletion is permanent, requires specific permissions, affects associated resources, or provides confirmation. For a destructive tool with zero annotation coverage, this is inadequate.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words. It's appropriately sized for a simple operation, though it could be more informative. The structure is front-loaded but lacks depth.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a destructive mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral risks, success/failure responses, or integration with sibling tools (e.g., 'get_environment' for verification). For a tool that permanently removes resources, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the single parameter 'environmentId' documented in the schema. The description adds no parameter semantics beyond what the schema provides (e.g., format examples or validation rules). With high schema coverage, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Delete an environment' clearly states the verb (delete) and resource (environment), which is adequate. However, it doesn't differentiate from sibling tools like 'delete_api', 'delete_api_version', or 'delete_schema_file', all of which perform deletion operations on different resources. The purpose is clear but lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an environment ID), exclusions, or related tools like 'get_environment' to verify existence first. With multiple deletion tools in the sibling list, the absence of usage context is a significant gap.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Delete' implies a destructive mutation, the description doesn't specify whether this operation is reversible, what permissions are required, whether it affects other resources, or what happens on success/failure. For a destructive operation with zero annotation coverage, this leaves critical behavioral aspects undocumented.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable. Every word earns its place by conveying essential information about what the tool does.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a destructive deletion tool with no annotations and no output schema, the description is incomplete. It doesn't address critical context like what happens after deletion (confirmation, error handling), whether the operation is atomic, what permissions are needed, or how it relates to other schema operations. The minimal description leaves too many open questions for safe and effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with all three parameters (apiId, schemaId, filePath) documented in the schema. The description adds no additional parameter information beyond what's already in the structured schema. According to scoring rules, when schema coverage is high (>80%), the baseline score is 3 even with no parameter details in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Delete a schema file' clearly states the action (delete) and the resource (schema file), making the purpose immediately understandable. It's specific enough to distinguish this from general deletion tools like 'delete_api' or 'delete_api_version' that target different resources. However, it doesn't explicitly differentiate from 'create_update_schema_file' which might handle deletion as part of an update operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'delete_api', 'delete_api_version', and 'create_update_schema_file' that might handle related operations, there's no indication of when this specific deletion tool is appropriate. No prerequisites, constraints, or comparison to other deletion methods are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('fork') but doesn't explain what happens during forking—whether it copies all elements, preserves history, requires source permissions, or affects the original collection. For a mutation tool with zero annotation coverage, this leaves critical behavioral traits unspecified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It front-loads the core action and destination, making it immediately understandable. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'fork' means operationally, what permissions are required, what the result looks like, or how it differs from similar tools. Given the complexity of forking and lack of structured data, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters (collection_id, workspace, label). The description adds no additional meaning beyond implying these are required for the fork operation. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('fork') and target resource ('a collection'), with a specific destination ('to a workspace'). It distinguishes from siblings like 'create_collection' by implying it duplicates an existing collection rather than creating a new one from scratch. However, it doesn't explicitly differentiate from 'fork_environment' or explain what 'fork' entails beyond the basic action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'create_collection' or 'merge_collection_fork'. It mentions a destination workspace but doesn't specify prerequisites, permissions needed, or typical use cases. The agent must infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It implies a write operation ('Create a fork') but doesn't disclose permissions needed, whether it's idempotent, rate limits, or what the output looks like. This leaves significant gaps for an agent to understand the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't explain what a 'fork' entails (e.g., copies settings, variables), potential side effects, or return values, leaving the agent with incomplete context for safe and effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so parameters are well-documented there. The description adds no additional parameter semantics beyond implying that 'environmentId' identifies what to fork and 'workspace' specifies where. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Create a fork') and target resource ('an environment in a workspace'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'fork_collection' or 'create_environment', which would require explicit comparison to achieve a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'create_environment' or 'fork_collection', nor does it mention prerequisites such as needing appropriate permissions. The description only states what it does, not when or why to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states this is a read operation ('Gets'), implying it's non-destructive, but doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions, or what 'details' include. This leaves significant gaps for a tool that retrieves billing information.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose. Every word earns its place, with no redundant or vague phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of billing data and lack of annotations or output schema, the description is insufficient. It doesn't explain what 'details' include, potential permissions needed, or return format. For a tool that likely involves sensitive financial information, more context is required.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description adds context by specifying the resource ('Postman billing account details') and scope ('for the given team'), which provides semantic value beyond the empty schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Gets') and resource ('Postman billing account details'), specifying it's for a given team. However, it doesn't distinguish this from sibling tools like 'get_user_info' or 'get_workspace', which also retrieve information but for different resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. The description mentions 'for the given team' but doesn't clarify if this is required or how it relates to other account-related tools like 'list_account_invoices'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden but only states it 'gets details' without disclosing behavioral traits like read-only nature, authentication needs, error handling, or rate limits. It's minimal and lacks transparency for safe agent operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with zero wasted words, front-loaded with the core action. It's appropriately sized for a simple tool, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 2 parameters, no annotations, and no output schema, the description is incomplete—it doesn't explain what 'details' returns, error cases, or behavioral context. It's inadequate given the lack of structured data to compensate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters (apiId and include). The description adds no additional meaning beyond implying 'specific API' relates to apiId, meeting the baseline for high schema coverage without extra value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get details of a specific API' clearly states the action (get) and resource (API), but it's vague about what 'details' includes and doesn't differentiate from siblings like get_api_version or get_api_schema. It's functional but lacks specificity about scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like get_api_version or get_api_schema, nor any context about prerequisites or exclusions. The description alone offers no usage instructions beyond the basic purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Get a specific collection', implying a read-only operation, but doesn't specify if it's safe, what permissions are needed, whether it's idempotent, or what the output format might be. This leaves significant gaps in understanding the tool's behavior beyond basic retrieval.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words, making it easy to parse. However, it could be more front-loaded with key details, such as specifying the API context or differentiating from siblings, but it's appropriately sized for its minimal content.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (3 parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain what a 'collection' entails, how it differs from other collection-related tools, or what the return value includes, leaving the agent with insufficient context to use the tool effectively beyond basic parameter input.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with parameters 'apiId', 'collectionId', and 'versionId' documented. The description doesn't add any meaning beyond the schema, such as explaining the relationships between these IDs or why 'versionId' is required for API viewers. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'Get a specific collection from an API', which provides a verb ('Get') and resource ('collection'), but it's vague about what 'collection' means in this API context and doesn't distinguish it from sibling tools like 'get_collection' or 'list_collections'. It specifies 'from an API' but lacks detail about the API's nature or the collection's content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing an API ID or collection ID, or differentiate it from similar tools like 'get_collection' or 'list_collections' in the sibling list, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the action ('Get comments') without detailing traits like pagination behavior (implied by 'cursor' and 'limit' parameters but not explained), authentication requirements, rate limits, or what the return format looks like. This is inadequate for a tool with multiple parameters and no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's front-loaded and directly states the tool's purpose without unnecessary elaboration, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (3 parameters, no output schema, and no annotations), the description is incomplete. It fails to address key contextual aspects like the nature of comments, pagination behavior, or return format, leaving significant gaps for an agent to understand how to effectively use this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents all parameters (apiId, cursor, limit) with basic descriptions. The description adds no additional meaning beyond the schema, such as explaining comment types or pagination context. This meets the baseline score of 3 since the schema handles parameter documentation adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get comments for an API' clearly states the verb ('Get') and resource ('comments for an API'), making the basic purpose understandable. However, it lacks specificity about what type of comments (e.g., user feedback, code annotations, review threads) and doesn't differentiate from sibling tools like 'get_api' or 'get_api_tags', leaving ambiguity about scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention if this is for retrieving all comments, filtered comments, or how it relates to sibling tools like 'create_api_comment' or 'update_api_comment'. The absence of context or exclusions leaves the agent without usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but only states the action without behavioral details. It doesn't disclose if this is a read-only operation, requires authentication, has rate limits, or what the output format looks like (e.g., JSON schema, bundled data). This leaves significant gaps for a tool that likely involves API interactions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words. It's front-loaded with the core action, making it easy to parse quickly, though this conciseness contributes to gaps in other dimensions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete for a tool with 4 parameters and likely complex behavior (e.g., retrieving API schemas). It fails to explain return values, error conditions, or how parameters interact, leaving the agent under-informed for proper invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema fully documents parameters like 'apiId', 'schemaId', 'versionId', and 'bundled'. The description adds no additional meaning beyond the schema, such as explaining relationships between parameters or usage examples, meeting the baseline for high coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get a specific schema from an API' clearly states the verb ('Get') and resource ('schema'), but it's vague about what 'specific schema' means compared to siblings like 'get_api_schema_files' or 'get_schema_file_contents'. It doesn't specify whether this retrieves metadata, content, or bundled formats, leaving the purpose ambiguous relative to alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus siblings such as 'get_api_schema_files' or 'get_schema_file_contents'. The description lacks context about prerequisites, alternatives, or exclusions, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action ('Get files') without detailing aspects like whether this is a read-only operation, if it supports pagination (implied by 'cursor' and 'limit' parameters but not explicitly stated), rate limits, authentication needs, or error handling. This leaves significant gaps for an agent to understand how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence: 'Get files in an API schema'. It is front-loaded with the core action and resource, with zero wasted words. This makes it easy to parse and understand at a glance, though it sacrifices detail for brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of a tool with 5 parameters (including pagination and role-based requirements), no annotations, and no output schema, the description is insufficient. It fails to explain critical aspects like what 'files' entail (e.g., metadata vs. content), how pagination works, or the response format. This leaves the agent with incomplete information for proper invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with all parameters documented in the input schema (e.g., 'apiId', 'schemaId', 'cursor', 'limit', 'versionId'). The description does not add any additional meaning beyond this, such as explaining relationships between parameters (e.g., that 'versionId' is required for certain roles) or usage examples. This meets the baseline for high schema coverage but lacks enhancement.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get files in an API schema' clearly states the action (get) and resource (files in an API schema), which is specific enough to understand the basic purpose. However, it does not differentiate this tool from potential siblings like 'get_schema_file_contents' or 'get_api_schema', which might handle related but distinct operations, leaving room for ambiguity in a crowded toolset.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools like 'get_schema_file_contents' (which might retrieve content) and 'get_api_schema' (which might retrieve schema metadata), the lack of context or exclusions makes it unclear how this tool fits into the workflow, leading to potential misuse.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. It only states the action ('Get tags') without mentioning whether this is a read-only operation, what permissions are required, how results are returned (e.g., list format, pagination), or error conditions. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately scannable. Every word earns its place by conveying essential information without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (single parameter, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks context about usage, behavior, or output format. Without annotations or output schema, the agent must guess at return values and operational details, making this incomplete for confident use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with the single parameter 'apiId' documented as 'API ID'. The description doesn't add any semantic context beyond this (e.g., explaining what an API ID is or where to find it). According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even without parameter details in the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get tags for an API' clearly states the verb ('Get') and resource ('tags for an API'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'get_workspace_tags' or 'update_api_tags' by specifying it's for API tags. However, it doesn't specify whether it retrieves all tags or filtered ones, which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an API ID), differentiate from similar tools like 'get_workspace_tags' or 'get_tagged_elements', or specify use cases. The agent must infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Get' which implies a read-only operation, but doesn't clarify if this requires authentication, what the output format is (e.g., JSON details of the version), or any error conditions (e.g., invalid IDs). For a tool with no annotations, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. There's zero waste, earning a high score for conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (2 required parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on usage, behavior, or output. Without annotations or an output schema, more context would be helpful, but it's not entirely incomplete for a simple retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear parameter names and descriptions ('API ID' and 'Version ID'). The description doesn't add any meaning beyond what the schema provides—it doesn't explain what an 'API ID' or 'Version ID' is, where to find them, or their format. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get a specific version of an API' clearly states the action (Get) and resource (a specific version of an API), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_api' or 'get_api_versions', but the focus on a 'specific version' provides some distinction. This is clear but lacks explicit sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an API ID and version ID), compare it to similar tools like 'get_api' (for general API info) or 'get_api_versions' (for listing versions), or specify any context for its application. Usage is implied by the name but not explained.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states 'Get all versions' but doesn't disclose behavioral traits such as pagination behavior (implied by 'cursor' and 'limit' parameters), rate limits, authentication needs, or whether it's read-only. This leaves significant gaps for a tool with 3 parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's front-loaded and appropriately sized for a simple retrieval tool, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations, no output schema, and 3 parameters, the description is incomplete. It lacks details on behavior (e.g., pagination, response format), usage context, and doesn't compensate for the absence of structured fields, making it inadequate for informed tool selection.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters (apiId, cursor, limit). The description adds no meaning beyond this, such as explaining what 'all versions' entails or how pagination works. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get all versions of an API' clearly states the action (get) and resource (versions of an API). It distinguishes from siblings like 'get_api_version' (singular) but doesn't explicitly contrast with other list-like tools such as 'list_apis' or 'get_api_schema_files', making it specific but not fully differentiated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an API ID), exclusions, or comparisons to siblings like 'get_api_version' (for a single version) or 'list_apis' (for listing APIs themselves), leaving usage context implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Get' implies a read operation, the description doesn't specify what authentication is required, what specific user information is returned, whether there are rate limits, or what format the response takes. For a tool with zero annotation coverage, this leaves significant behavioral questions unanswered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise at just 5 words: 'Get authenticated user information.' It's front-loaded with the essential action and resource, with zero wasted words. Every word earns its place in this minimal but complete statement of purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'authenticated user information' includes, how it differs from other user-related tools, what authentication method is required, or what the response format will be. The agent would need to guess or trial-and-error to use this tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the parameter situation (none needed). The description doesn't need to compensate for any parameter gaps. A baseline of 4 is appropriate since the description correctly doesn't waste space discussing non-existent parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get authenticated user information' clearly states the verb ('Get') and resource ('authenticated user information'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_user_info' or 'get_accounts' - the description is generic and doesn't specify what distinguishes this particular user information retrieval from others.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_user_info' and 'get_accounts' available, there's no indication whether this tool returns different data, requires different permissions, or serves a different use case. The agent receives no help in selecting between similar-looking tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'Get details' but does not specify what details are returned, whether it's a read-only operation, authentication requirements, or potential errors. For a tool with no annotations, this is insufficient to inform the agent about its behavior beyond the basic action.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence: 'Get details of a specific collection.' It is front-loaded with the core action and resource, with no unnecessary words or fluff. This makes it highly efficient and easy to parse, earning a top score for conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It does not explain what 'details' are returned, how the tool behaves with different parameters, or any error conditions. For a tool that retrieves data, more context on the response format and usage scenarios is needed to be fully helpful to an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, detailing each parameter's purpose and constraints (e.g., 'collection_id' as required, 'access_key' for read-only access, 'model' with enum). The description adds no additional meaning beyond the schema, so it meets the baseline of 3, as the schema adequately documents the parameters without extra context from the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool's purpose as 'Get details of a specific collection,' which is clear but vague. It specifies the verb ('Get') and resource ('collection'), but does not distinguish it from siblings like 'get_collection_folder' or 'get_collection_request,' which also retrieve details about related resources. The purpose is understandable but lacks specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With siblings such as 'list_collections' (for listing multiple collections) and other 'get_' tools for specific collection components, there is no indication of context, prerequisites, or exclusions. This leaves the agent without direction on tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure but only states it 'gets details' without specifying what details are returned, whether authentication is required, rate limits, error conditions, or whether this is a read-only operation. The description doesn't contradict annotations (none exist), but provides minimal behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a straightforward retrieval operation and gets directly to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 5 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain what 'details' are returned, how the optional parameters affect the response, or provide any context about the folder structure or relationships. The description leaves too many open questions for effective tool use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 100% description coverage, so all parameters are documented in the structured schema. The description adds no additional parameter semantics beyond what's already in the schema descriptions. This meets the baseline of 3 when schema coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get details') and resource ('specific folder in a collection'), making the purpose unambiguous. However, it doesn't differentiate this tool from similar sibling tools like 'get_collection' or 'get_collection_request', which also retrieve details about collection-related resources.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools that retrieve collection-related data (e.g., get_collection, get_collection_request, get_collection_response), there's no indication of when this specific folder-focused tool is appropriate versus other retrieval operations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool 'gets a list,' implying a read-only operation, but doesn't clarify if it's safe, requires authentication, has rate limits, or what the output format looks like (e.g., paginated list). The description adds minimal value beyond the basic action, missing key behavioral details for a tool with multiple parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, straightforward sentence ('Get a list of collection forks') that efficiently conveys the core action. It's front-loaded with the main purpose and avoids unnecessary words, making it easy to parse. However, it could be slightly more informative without sacrificing brevity, such as by hinting at pagination or sorting features.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no annotations, no output schema), the description is insufficient. It doesn't explain the return values (e.g., what data the list contains), behavioral aspects like pagination or sorting implied by parameters, or how it fits into the broader API context (e.g., relation to 'fork_collection'). For a list operation with multiple options, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear documentation for all 5 parameters (e.g., 'collection_id' as 'Collection ID'). The description adds no parameter-specific information beyond implying a list operation, so it doesn't enhance the schema's details. This meets the baseline score of 3, as the schema adequately covers parameter semantics without description assistance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get a list of collection forks' clearly states the verb ('Get') and resource ('collection forks'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_environment_forks' or 'fork_collection', leaving ambiguity about what specifically distinguishes this tool from related operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a collection ID), contrast with similar tools like 'get_collection' or 'fork_collection', or specify use cases (e.g., viewing forks after creation). This lack of context leaves the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'Get details,' implying a read-only operation, but doesn't clarify if it requires authentication, has rate limits, returns error conditions, or what the output format might be. This is a significant gap for a tool with multiple parameters and no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly. Every part of the sentence contributes to understanding the tool's basic function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of 5 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address behavioral aspects like authentication needs, error handling, or output structure, which are critical for an agent to use the tool effectively. The high schema coverage helps, but the description fails to compensate for the lack of other structured data.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100%, meaning all parameters are documented in the schema itself. The description adds no additional meaning about parameters beyond implying a focus on 'details' of a request. This meets the baseline of 3, as the schema handles the heavy lifting, but the description doesn't enhance understanding of how parameters like 'ids' or 'populate' affect the retrieved details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get details') and resource ('specific request in a collection'), making the purpose understandable. However, it doesn't distinguish this tool from similar siblings like 'get_collection' or 'get_collection_response', which also retrieve collection-related data, so it doesn't achieve full differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as needing a valid collection and request ID, or compare it to siblings like 'get_collection' for broader collection details or 'get_collection_response' for response-specific data. This leaves the agent without context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states a read operation ('Get details'), implying it is non-destructive, but does not cover critical aspects like authentication needs, rate limits, error handling, or response format. This leaves significant gaps for an agent to understand operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, direct sentence with no wasted words, clearly front-loading the core action and resource. It is appropriately sized for its purpose, making it efficient and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete for a tool with 5 parameters and no behavioral context. It fails to address key aspects like what 'details' include, response structure, or error scenarios, leaving the agent with insufficient information for reliable invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema fully documents all 5 parameters. The description adds no additional semantic context beyond implying the need for collection and response IDs. Since the schema handles parameter documentation adequately, a baseline score of 3 is appropriate, as the description does not compensate but also does not detract.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and the resource 'details of a specific response in a collection', making the purpose understandable. However, it does not explicitly differentiate from sibling tools like 'get_collection_request' or 'get_collection_folder', which have similar naming patterns but target different resources, leaving some ambiguity in sibling context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, such as other 'get_' tools for related resources (e.g., 'get_collection' or 'get_collection_request'). It lacks explicit context, prerequisites, or exclusions, offering minimal usage direction beyond the basic purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states 'Get roles' which implies a read-only operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, pagination, or error handling. For a tool with no annotations, this leaves significant gaps in understanding how it behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no wasted words. It's front-loaded and efficiently conveys the core purpose without unnecessary elaboration, making it easy to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete. It doesn't explain what 'roles' includes (e.g., permissions, user assignments), the return format, or error cases. For a tool that likely returns structured data about roles, more context is needed to understand its full functionality.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with 'collectionId' documented as 'The collection ID'. The description doesn't add any meaning beyond this, such as format examples or constraints. With high schema coverage, a baseline score of 3 is appropriate as the schema handles parameter documentation adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get roles for a collection' clearly states the action (get) and target (roles for a collection), which is adequate. However, it doesn't differentiate from sibling tools like 'get_workspace_roles' or 'list_workspace_roles', leaving ambiguity about scope. The purpose is understandable but lacks specificity about what 'roles' entail in this context.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. With siblings like 'get_workspace_roles' and 'list_workspace_roles', the description doesn't clarify if this is for collection-specific roles, workspace-level roles, or other distinctions. There's no mention of prerequisites or context for usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Get details') but doesn't clarify whether this is a read-only operation, what permissions are required, how errors are handled, or the format of returned details. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose without any redundant or unnecessary information. It is appropriately sized and front-loaded, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what 'details' are returned, how they are structured, or any behavioral aspects like error conditions or authentication requirements. For a tool that presumably returns environment metadata, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, fully documenting the single 'environmentId' parameter with format examples. The description adds no additional parameter semantics beyond what the schema already provides, so it meets the baseline score of 3 for high schema coverage without compensating value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('details of a specific environment'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'list_environments' or 'get_environment_forks', which would require explicit comparison to achieve a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'list_environments' (for multiple environments) or 'get_environment_forks' (for fork details). It lacks any mention of prerequisites, exclusions, or contextual triggers, leaving the agent to infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get'), implying it's non-destructive, but doesn't cover critical aspects like authentication requirements, rate limits, pagination behavior (beyond what the schema implies), error handling, or return format. For a tool with 5 parameters and no output schema, this leaves significant gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with zero wasted words. It's front-loaded with the core purpose ('Get a list of environment forks'), making it easy to parse. Every word earns its place, and there's no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'environment forks' are, how results are structured, or behavioral traits like pagination or error cases. While the schema covers parameters, the lack of output schema and annotations means the description should do more to guide usage and expectations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, clearly documenting all 5 parameters (e.g., 'environmentId' format, 'cursor' for pagination). The description adds no additional parameter semantics beyond what's in the schema, such as explaining what 'environment forks' are or how sorting/pagination works in practice. With high schema coverage, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get a list of environment forks' clearly states the verb ('Get') and resource ('environment forks'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'fork_environment' (which creates forks) or 'merge_environment_fork' (which merges forks), leaving the specific role ambiguous. It's adequate but lacks sibling differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an environment ID), exclusions, or compare it to related tools like 'get_environment' or 'list_environments'. Without this context, the agent must infer usage from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states a read operation ('Get'), implying it's likely non-destructive, but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or output format. The description is minimal and lacks necessary context for safe and effective use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with no wasted words. It's front-loaded and directly states the purpose, though it could be more specific. The brevity is appropriate but borders on under-specification given the lack of other details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete. It doesn't explain what 'contents' means (e.g., file data format), behavioral aspects like permissions or errors, or how it fits with sibling tools. For a tool with 4 parameters and read operation, more context is needed to ensure proper use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents all parameters (apiId, schemaId, filePath, versionId) with basic descriptions. The description adds no additional meaning beyond implying these are needed to locate the file, which is already clear from the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get contents of a schema file' clearly states the action (get) and resource (schema file contents), but it's somewhat vague about what 'contents' entails (e.g., raw text, structured data). It distinguishes from siblings like 'get_api_schema_files' (which likely lists files) but not explicitly, and doesn't specify scope beyond the file.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention how it differs from 'get_api_schema' or 'get_api_schema_files', nor does it specify prerequisites like authentication or context. The description alone offers no usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get elements by tag' implies a read-only operation but doesn't specify permissions, rate limits, pagination behavior (beyond the cursor param in schema), or what 'elements' entail (e.g., structured data, IDs). It lacks critical context for safe and effective use.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single phrase, 'Get elements by tag', which is front-loaded and wastes no words. However, this brevity contributes to underspecification rather than clarity, but it earns full marks for conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'elements' are, their structure, or how results are returned (e.g., list of objects). This leaves significant gaps for the agent to infer behavior, especially without annotations or output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all 5 parameters (slug, limit, direction, cursor, entityType). The description adds no additional meaning beyond the schema, such as explaining tag slug format or entityType implications. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get elements by tag' restates the tool name 'get_tagged_elements' without adding specificity. It doesn't clarify what 'elements' refers to (e.g., API elements, collection items) or distinguish this tool from sibling tools like 'get_api_tags' or 'get_workspace_tags', which also handle tags. This is a tautology with minimal differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context (e.g., workspace vs. API scope), or compare it to sibling tools like 'list_pan_elements' or 'get_api_tags'. This leaves the agent guessing about appropriate use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves status but doesn't explain what 'status' entails (e.g., pending, completed, failed), whether it's read-only (implied by 'get'), any rate limits, authentication needs, or response format. This leaves significant gaps for a tool interacting with asynchronous tasks.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste—it directly states the tool's purpose without redundancy or fluff. It's appropriately front-loaded and sized for a simple retrieval tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of asynchronous task status (which often involves states like progress or errors), no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, return values, or usage context, making it inadequate for an agent to fully understand how to invoke and interpret results from this tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with parameters 'apiId' and 'taskId' documented as 'API ID' and 'Task ID'. The description adds no additional meaning beyond this, such as explaining where to obtain these IDs or their format. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('status of an asynchronous task'), making the purpose specific and understandable. However, it doesn't distinguish this tool from potential siblings like 'get_api' or 'get_collection' beyond the resource type, as all 'get_' tools share similar retrieval patterns without explicit differentiation in the description.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing task ID), exclusions, or related tools for task management, leaving the agent to infer usage from the name alone in a context with many sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves information but doesn't specify what information is returned, whether it's read-only, if there are rate limits, or any error conditions. This leaves significant gaps for an agent to understand the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to parse quickly, which is ideal for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what information is returned, the format of the response, or any behavioral traits like error handling. For a tool that likely returns user-specific data, more context is needed to guide an agent effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate here, but it also doesn't provide any extra context about inputs, so it doesn't exceed the baseline for a parameterless tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('information about the authenticated user'), making the purpose unambiguous. However, it doesn't distinguish itself from the sibling tool 'get_authenticated_user', which appears to serve a similar function, preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'get_authenticated_user' or other user-related tools. It lacks context about prerequisites, such as authentication requirements, and doesn't mention any exclusions or specific use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It states the tool retrieves details but doesn't specify what those details include, whether it's a read-only operation, any authentication requirements, rate limits, or error conditions. This leaves significant gaps for an agent to understand how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It's appropriately sized for a simple retrieval tool, with no wasted space or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (a basic read operation with 2 parameters) and the schema's full coverage, the description is minimally adequate. However, with no annotations and no output schema, it lacks context about what details are returned, potential errors, or behavioral traits. This makes it incomplete for optimal agent use, though not critically deficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear documentation for both parameters ('workspace' as ID and 'include' for additional data). The description doesn't add any meaningful semantic context beyond this, such as examples of what 'include' might accept or how the workspace ID is formatted. Since the schema does the heavy lifting, the baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('details of a specific workspace'), making it immediately understandable. However, it doesn't distinguish this tool from similar siblings like 'get_workspace_roles' or 'get_workspace_tags', which also retrieve workspace-related information but focus on different aspects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. For example, it doesn't clarify when to choose 'get_workspace' over 'list_workspaces' (for a single workspace vs. multiple) or 'get_workspace_roles' (for details vs. role information). There's no mention of prerequisites, context, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states a read operation ('Get'), which implies safety, but doesn't disclose behavioral traits like authentication requirements, rate limits, error handling, or response format. For a tool with no annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It is front-loaded with the core action and resource, making it easy to parse. Every word earns its place without redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is incomplete. It lacks details on behavioral traits, response format, and usage context. For a tool with 2 parameters and no structured safety or output information, the description should provide more guidance to be fully helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters ('workspaceId' and 'includeScim'). The description adds no additional meaning beyond implying the 'workspaceId' parameter's purpose. With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate with extra context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Get' and resource 'roles for a specific workspace', making the purpose explicit. It distinguishes from siblings like 'list_workspace_roles' by specifying retrieval for a single workspace rather than listing all. However, it doesn't fully differentiate from 'get_collection_roles' or 'update_workspace_roles' beyond the resource name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like 'list_workspace_roles' or 'get_collection_roles'. The description implies usage for a specific workspace but lacks explicit context, prerequisites, or exclusions, leaving the agent to infer based on parameter names alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description 'Get workspace tags' provides no information about what this operation returns (list of tags? tag objects with metadata?), whether it's paginated, what permissions are required, rate limits, or any other behavioral characteristics. It's a minimal statement that offers no transparency beyond the basic action implied by the name.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at just three words. While it's under-specified in terms of content, it's perfectly efficient in terms of word economy. There's zero wasted language or unnecessary elaboration. The structure is simple and direct.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no annotations and no output schema, the description is inadequate. It doesn't explain what the tool returns (critical information since there's no output schema), doesn't provide usage context, and doesn't disclose any behavioral characteristics. While the parameter is well-documented in the schema, the overall description fails to provide the contextual information needed for an agent to understand and use this tool effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage with the workspaceId parameter clearly documented as 'Workspace ID'. The description 'Get workspace tags' doesn't add any meaningful semantic information about the parameter beyond what the schema already provides. It implies the workspaceId is needed to get tags for that workspace, but this is already obvious from the schema. Baseline score of 3 is appropriate when schema coverage is complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get workspace tags' is a tautology that essentially restates the tool name. It specifies the verb 'Get' and resource 'workspace tags', but doesn't provide any additional clarity about what this operation actually does beyond the obvious interpretation of the name. It doesn't distinguish this tool from sibling tools like 'get_api_tags' or 'get_tagged_elements'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance about when to use this tool versus alternatives. There are multiple tag-related tools in the sibling list (get_api_tags, get_tagged_elements, update_workspace_tags), but the description doesn't explain when this specific workspace tags retrieval tool is appropriate versus those other options. No context, prerequisites, or exclusions are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses that this is a diagnostic operation that returns system information and configuration status, which helps the agent understand it's a read-only check. However, it doesn't mention potential side effects (though likely none), authentication requirements, rate limits, or error behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise with two sentences that each earn their place: the first states the action and purpose, the second specifies the return value. It's front-loaded with the core functionality and wastes no words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given this is a simple diagnostic tool with no parameters, no annotations, and no output schema, the description provides adequate context about what it does and what it returns. However, without an output schema, more detail about the structure of the returned system information would be helpful for completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage. The description appropriately doesn't discuss parameters since none exist. It adds value by explaining what the tool does without needing to compensate for parameter documentation gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the specific action ('Perform a local system health check') and the resource ('Postman MCP server configuration and connectivity'), distinguishing it from sibling tools that focus on API/collection/environment management rather than system diagnostics. It explicitly mentions what it verifies and what it returns.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by stating it's for verifying server configuration and connectivity, suggesting it should be used for diagnostic purposes. However, it doesn't explicitly state when not to use it or name specific alternatives among the many sibling tools, which are all data operations rather than system checks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description states it 'Gets all invoices' but doesn't specify whether this is a read-only operation, what permissions are required, whether results are paginated, or what format the output takes. For a tool that retrieves potentially sensitive billing data, this lack of behavioral context is significant.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that conveys the core functionality without unnecessary words. It's appropriately sized for a simple retrieval tool and front-loads the essential information. Every word earns its place in this concise formulation.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that this is a data retrieval tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns (invoice objects, summaries, or raw data), whether authentication is required, or how errors are handled. For a billing-related tool that likely requires specific permissions, this represents a significant contextual gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters (accountId and status) with descriptions and enum values. The description mentions filtering by status, which aligns with the schema but doesn't add meaningful semantic context beyond what's already in the structured fields. The baseline of 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Gets') and resource ('invoices for a Postman billing account'), and specifies filtering by status. It distinguishes from generic 'get' operations by mentioning the filtering aspect. However, it doesn't explicitly differentiate from potential sibling tools like 'get_accounts' or other invoice-related tools that might exist.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, appropriate contexts, or exclusions. While it implies filtering by status, it doesn't explain when this filtering is necessary or what happens without it. No sibling tools are referenced for comparison.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. While 'List all APIs' implies a read-only operation, it doesn't address critical behaviors like pagination (though the schema includes 'cursor' and 'limit'), authentication requirements, rate limits, error conditions, or what the output format looks like (no output schema exists). This leaves significant gaps for an agent to understand how to properly invoke and interpret results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at just 6 words, front-loading the core purpose without any wasted words. Every element ('List', 'all', 'APIs', 'in a workspace') contributes essential information, making it efficient and immediately understandable despite its brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no annotations, no output schema), the description is insufficiently complete. While concise, it lacks necessary context about behavioral traits, output format, error handling, and differentiation from sibling tools. For a list operation with filtering parameters and no output schema, more guidance on result interpretation and tool selection would be needed for proper agent usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents all 5 parameters. The description adds no additional parameter information beyond what's in the schema - it doesn't explain parameter relationships, filtering logic, or usage examples. The baseline score of 3 reflects adequate coverage through the schema alone, with no value added by the description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List all') and resource ('APIs in a workspace'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_api' or 'get_api_versions' that might retrieve specific APIs or versions, leaving some ambiguity about when to choose this tool over those alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools like 'get_api' (for single API retrieval) and 'get_api_versions' (for version-specific data), the description lacks any context about selection criteria, prerequisites, or typical use cases for listing versus getting APIs.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions optional filtering but fails to disclose critical behavioral traits: whether this is a read-only operation, if it requires specific permissions, pagination behavior (cursor parameter implies it but isn't explained), rate limits, or what the output format looks like. For a listing tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose ('List collection access keys') and adds a qualifying clause ('with optional filtering by collection ID'). There is zero waste or redundancy, making it appropriately concise for a listing tool with straightforward parameters.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (listing with filtering and pagination), no annotations, and no output schema, the description is incomplete. It doesn't explain the return format, pagination mechanics, error conditions, or authentication requirements. For a tool that likely returns structured data (access keys), the lack of output details leaves significant gaps for an AI agent to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters (collectionId for filtering, cursor for pagination). The description adds marginal value by explicitly mentioning 'optional filtering by collection ID', which aligns with the schema but doesn't provide additional semantic context beyond what's in the parameter descriptions. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'List collection access keys' specifies the verb (list) and resource (collection access keys). It distinguishes from siblings like 'get_collection' or 'get_collection_roles' by focusing specifically on access keys, though it doesn't explicitly contrast with similar listing tools like 'list_collections' or 'list_workspace_roles'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides minimal guidance: 'with optional filtering by collection ID' hints at when filtering might be useful, but offers no explicit when-to-use rules, prerequisites, or alternatives. It doesn't clarify when to use this versus other access-related tools like 'get_collection_roles' or 'delete_collection_access_key', leaving usage context largely implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It mentions 'Supports filtering and pagination,' which adds some behavioral context, but does not disclose critical details like authentication requirements, rate limits, response format, error handling, or whether it's a read-only operation. For a list tool with no annotations, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the core purpose in the first sentence. The second sentence adds useful context without redundancy. It is appropriately sized for a list tool, though it could be slightly more informative without losing efficiency.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is incomplete. It does not explain the return values, error conditions, or behavioral constraints. For a tool with four parameters and no structured output documentation, more context is needed to guide effective use by an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema fully documents all four parameters. The description adds minimal value by implying filtering and pagination capabilities but does not provide additional semantics beyond what the schema already states. This meets the baseline for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'List all collections in a workspace.' It specifies the verb ('List') and resource ('collections'), and includes the scope ('in a workspace'). However, it does not explicitly differentiate from sibling tools like 'get_collection' or 'list_workspaces,' which reduces clarity slightly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions filtering and pagination but does not specify when to choose this over other list tools (e.g., 'list_apis' or 'list_environments') or when to use 'get_collection' for a single collection. No exclusions or prerequisites are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It describes the default workspace behavior, but doesn't disclose other behavioral traits like pagination, rate limits, authentication requirements, sorting, or return format. For a list operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is perfectly concise with two clear sentences. The first states the core purpose, the second explains the optional parameter's default behavior. Every word earns its place with zero redundancy or wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with one optional parameter and 100% schema coverage, the description covers the basic purpose and default behavior adequately. However, without annotations or output schema, it lacks information about authentication, rate limits, pagination, and return format that would be helpful for complete understanding.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with the single parameter 'workspace' fully documented in the schema. The description adds minimal value beyond the schema by mentioning the default behavior when workspace is unspecified, but doesn't provide additional semantic context about workspace IDs or filtering options. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('List') and resource ('environments'), specifying scope ('all environments in a workspace'). It distinguishes from siblings like 'get_environment' (singular) and 'list_workspaces' (different resource), but doesn't explicitly contrast with similar list tools like 'list_collections' or 'list_apis'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by specifying the default workspace behavior ('If workspace not specified, lists environments in "My Workspace"'), but doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_environment' (for a single environment) or other list tools. No exclusions or prerequisites are mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Get all' implies a read-only operation, it doesn't mention pagination behavior (despite offset/limit parameters), rate limits, authentication requirements, or what 'all' means in practice (e.g., recursive vs flat listing). This leaves significant gaps for a tool with 12 parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that states the core purpose without unnecessary words. It's front-loaded with the essential information ('Get all elements and folders') and contains no redundant or verbose phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with 12 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain what 'elements' include (e.g., APIs, collections, workspaces), how folders are structured, whether results are paginated, or what the return format looks like. The agent must rely entirely on the input schema and trial-and-error.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with each parameter well-documented in the schema itself. The description adds no additional parameter information beyond implying a listing operation. This meets the baseline of 3 since the schema does the heavy lifting, but the description doesn't enhance understanding of how parameters interact or their practical use.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Get') and resource ('all elements and folders in Private API Network'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_tagged_elements' or 'list_apis' that might retrieve similar resources, preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools that retrieve API-related resources (e.g., 'list_apis', 'get_tagged_elements'), there's no indication of when this specific listing is appropriate, leaving the agent to guess based on context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states a read operation ('Get') but doesn't disclose behavioral traits such as authentication requirements, rate limits, response format, or whether it's idempotent. For a tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary details. It could be slightly improved by structuring usage context, but it earns its place by being direct and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It states what the tool does but lacks context on when to use it, behavioral details, or output expectations, making it incomplete for effective agent use without additional inference.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema description coverage, so the schema fully documents the inputs. The description adds no parameter-specific information, but with no parameters, a baseline score of 4 is appropriate as there's nothing to compensate for.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Get all available workspace roles') and specifies the scope ('based on team's plan'), which distinguishes it from generic role-fetching tools. However, it doesn't explicitly differentiate from sibling tools like 'get_workspace_roles' or 'update_workspace_roles', which would require more specific context about what 'available' means versus 'get'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'get_workspace_roles' or 'get_collection_roles'. It mentions 'based on team's plan' but doesn't explain if this is for planning purposes, role assignment, or other contexts, leaving usage unclear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states 'List all workspaces' but doesn't disclose behavioral traits like pagination, rate limits, authentication needs, response format, or whether it's read-only (implied but not explicit). For a list tool with zero annotation coverage, this is a significant gap in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste—'List all workspaces' is front-loaded and appropriately sized for a simple tool. Every word earns its place, making it highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's low complexity (list operation with optional filters) and rich schema (100% coverage), the description is minimally complete. However, with no annotations and no output schema, it lacks behavioral context (e.g., response format) that would help an agent. It's adequate but has clear gaps for a tool with three parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, with all three parameters ('type', 'createdBy', 'include') documented in the schema. The description adds no parameter semantics beyond what the schema provides (e.g., it doesn't explain filter logic or 'include' options). Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'List all workspaces' clearly states the verb ('List') and resource ('workspaces'), providing a basic purpose. However, it's vague about scope ('all' could mean unfiltered or comprehensive) and doesn't distinguish from sibling tools like 'get_workspace' (singular) or 'get_workspace_roles' (different resource). It's adequate but lacks specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools (e.g., 'get_workspace' for a single workspace or 'list_collections' for related resources), prerequisites, or exclusions. Usage is implied by the name alone, with no explicit context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Merge') but lacks details on permissions, side effects (e.g., data loss), rate limits, or response format. This is inadequate for a mutation tool with potential impacts.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse without unnecessary elaboration.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description is incomplete. It lacks behavioral details (e.g., effects, errors) and usage context, leaving significant gaps for an agent to understand how and when to invoke it safely.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters. The description doesn't add meaning beyond the schema, such as explaining the parent-child relationship implied by 'source' and 'destination' or clarifying merge strategies. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Merge') and resource ('a forked collection back into its parent'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'merge_environment_fork' or 'fork_collection', which would require a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a forked collection), exclusions, or comparisons to siblings like 'merge_environment_fork' or 'fork_collection', leaving the agent with minimal context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('merge') but doesn't explain what merging entails, such as whether it overwrites data, requires permissions, has side effects like deleting the source, or what happens on success/failure. The 'strategy' parameter hints at deletion behavior, but this isn't elaborated in the description, leaving critical gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that efficiently conveys the core action without unnecessary words. It is front-loaded and wastes no space, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of merging environments (a mutation operation with potential data loss), no annotations, and no output schema, the description is insufficient. It doesn't cover behavioral aspects like error conditions, return values, or the implications of the merge strategy, leaving the agent under-informed for safe and effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, so parameters are well-documented in the schema itself. The description adds no additional semantic context beyond implying a merge between source and destination environments, which is already clear from the schema. This meets the baseline score of 3 for high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('merge') and the resource ('a forked environment back into its parent'), making the purpose understandable. It distinguishes from sibling tools like 'fork_environment' and 'merge_collection_fork' by specifying the environment context, though it doesn't explicitly differentiate from 'merge_collection_fork' beyond the resource type.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'merge_collection_fork' or other environment-related tools. It lacks context on prerequisites, such as requiring a forked environment to exist, or exclusions, leaving the agent to infer usage from the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states this is a partial update operation, which implies mutation behavior, but doesn't disclose important behavioral traits like required permissions, whether changes are reversible, rate limits, or what happens to fields not provided. For a mutation tool with zero annotation coverage, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with two clear sentences that efficiently communicate the core functionality. Every word earns its place, and the information is front-loaded with no wasted text.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions, side effects, or response format. While concise, it lacks the contextual information needed for safe and effective tool invocation in a complex environment with many sibling tools.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters ('collection_id' and 'collection'). The description adds minimal value by implying partial updates apply to the 'collection' parameter fields, but doesn't provide additional semantic context beyond what the schema specifies. Baseline 3 is appropriate when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Partially update') and resource ('a collection'), and specifies the partial update behavior ('Only updates provided fields'). It distinguishes from full update operations but doesn't explicitly differentiate from sibling tools like 'update_collection' which might be a full update alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives like 'update_collection' or 'create_collection'. The description mentions partial updates but doesn't specify scenarios where partial updates are preferred over full updates or when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'pull changes' implies a read operation that might update the forked collection, it doesn't specify whether this is a destructive or safe operation, what permissions are required, how conflicts are handled, or what the expected outcome looks like. For a tool that likely modifies data, this leaves significant behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a tool with one parameter and no complex behavioral nuances to explain.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's apparent complexity (involving collection forks and synchronization), lack of annotations, and no output schema, the description is minimally adequate but incomplete. It covers the basic purpose but fails to address behavioral aspects, usage context among siblings, or expected outcomes, leaving the agent with insufficient information for confident invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?