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. 'Add new tasks' implies a write/mutation operation, but the description doesn't address permissions needed, whether tasks are appended or replace existing ones, error handling, or what happens on success/failure. This leaves significant behavioral 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, efficient sentence that communicates the core purpose without any wasted words. It's appropriately sized and front-loaded with the essential information.

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 insufficiently complete. It doesn't explain what the tool returns, error conditions, or important behavioral aspects like whether tasks are validated or how they integrate with existing project structure. The 100% schema coverage helps but doesn't compensate for these gaps.

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 both parameters and their nested structures. The description adds no additional parameter information beyond what's in the schema, maintaining the baseline score of 3 for adequate but not enhanced parameter semantics.

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 ('Add') and resource ('tasks to an existing project'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_task' or 'update_task' which might also involve task creation/modification, so it doesn't reach the highest 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 'create_task' or 'update_task'. It mentions 'existing project' but doesn't specify prerequisites, constraints, or appropriate contexts for bulk task addition versus single task 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 the full burden of behavioral disclosure. It effectively describes key traits: it's a mutation operation (implied by 'approve'), requires specific prerequisites ('marked as done'), and notes it's CLI-only with human intervention, which adds important context about execution constraints and user involvement.

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 appropriately sized with two sentences that are front-loaded: the first states the purpose and prerequisites, and the second adds critical behavioral context. Every sentence earns its place by providing 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 complexity (a mutation tool with prerequisites), no annotations, and no output schema, the description is mostly complete. It covers purpose, usage conditions, and behavioral traits like CLI-only and human intervention. However, it lacks details on what happens after approval (e.g., status changes) or error cases, leaving minor gaps.

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 (projectId and taskId) with examples. The description does not add any meaning beyond what the schema provides, such as explaining relationships between parameters or additional constraints, 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 clearly states the specific action ('Approve a completed task') and the resource ('task'), distinguishing it from siblings like 'update_task' or 'finalize_project'. It specifies that tasks must be marked as 'done' with completedDetails, adding precision beyond just the verb.

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 clear context for when to use this tool: only after a task is marked as 'done' with completedDetails. It implies an alternative (not approving if not done) but does not explicitly name sibling tools like 'update_task' for marking tasks as done, nor does it specify when not to use it (e.g., for pending tasks).

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 mentions creation but fails to detail critical aspects like permissions required, whether the project is mutable after creation, error handling, or what happens if tasks fail. This is inadequate 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 brief and front-loaded with the core purpose in the first sentence, followed by contextual guidance. Both sentences earn their place, though it could be slightly more structured for clarity.

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 lacks details on behavioral traits, error conditions, return values, and how it integrates with sibling tools, making it incomplete for effective agent 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 all parameters. The description adds minimal value by mentioning 'initial prompt and a list of tasks,' which aligns with the schema but doesn't provide additional semantics or usage examples beyond what's already structured.

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 project') and specifies key components ('with an initial prompt and a list of tasks'), which distinguishes it from basic creation tools. However, it doesn't explicitly differentiate from sibling tools like 'create_task' or 'generate_project_plan' beyond mentioning it's 'typically the first step'.

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 implied guidance by stating this is 'typically the first step in any workflow,' which suggests a temporal context for usage. However, it lacks explicit when-to-use rules, alternatives (e.g., vs. 'create_task'), or prerequisites, leaving gaps in operational clarity.

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 that the tool 'creates' something, implying a write/mutation operation, but doesn't mention any behavioral traits like permissions required, whether the creation is idempotent, error handling, or what happens if the project doesn't exist. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves beyond its basic function.

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 ('Create a new task within an existing project') and adds optional details without redundancy. Every part earns its place by clarifying scope and features, making it easy to parse quickly. It could be slightly improved by structuring prerequisites more explicitly, but it avoids unnecessary verbosity.

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 (creating a task) with no annotations and no output schema, the description is incomplete. It doesn't address key contextual aspects like what the tool returns (e.g., a task ID or confirmation), error conditions (e.g., invalid projectId), or side effects. The high schema coverage helps with parameters, but overall, the description lacks sufficient detail for safe and effective use in a complex environment with multiple 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%, meaning all parameters are documented in the input schema. The description adds minimal value by mentioning 'tool and rule recommendations' as optional features, which corresponds to the 'toolRecommendations' and 'ruleRecommendations' parameters. However, it doesn't provide additional context beyond what the schema already specifies (e.g., format examples or constraints), so it meets the baseline for high schema coverage without compensating further.

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 task') and the target resource ('within an existing project'), which provides a specific verb+resource combination. It also mentions optional features ('tool and rule recommendations'), adding useful detail. However, it doesn't explicitly distinguish this tool from sibling tools like 'add_tasks_to_project' or 'update_task', which could create ambiguity about when to use each.

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 'add_tasks_to_project' or 'update_task'. It mentions that tasks are created 'within an existing project', which implies a prerequisite (a project must exist), but doesn't state this explicitly or offer any context about exclusions or preferred scenarios. Without such guidance, the agent must infer usage from tool 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates a destructive operation ('Delete') but lacks details on permissions required, whether deletion is reversible, confirmation prompts, error handling, or side effects beyond tasks. 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—it directly states the action and scope without unnecessary words. 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?

For a destructive tool with no annotations and no output schema, the description is incomplete. It lacks critical behavioral context (e.g., irreversible deletion, permissions) and does not explain return values or error cases. Given the complexity and risk of deletion, more information is needed for safe agent 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 the parameter 'projectId' fully documented in the schema. The description does not add any parameter-specific details beyond what the schema provides, such as format examples or validation rules. Baseline 3 is appropriate when 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 clearly states the specific action ('Delete') and resource ('a project and all its associated tasks'), distinguishing it from sibling tools like delete_task (which only deletes individual tasks) and create_project (which creates rather than deletes). It precisely defines the scope of deletion beyond just the project itself.

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 that it deletes 'all its associated tasks,' suggesting it should be used when removing an entire project structure rather than individual components. However, it does not explicitly state when not to use it (e.g., vs. delete_task for partial cleanup) or name alternatives, keeping it from a perfect score.

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. 'Remove' implies a destructive operation, but it doesn't clarify if deletion is permanent/reversible, what happens to dependent data, or if specific permissions are required. For a mutation 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 appropriately sized for a simple delete operation and front-loads the core action and target resource.

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 insufficient. It doesn't address critical context like deletion consequences, error conditions, or return values. Given the complexity of a delete operation and lack of structured safety hints, more completeness 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 both parameters clearly documented in the schema. The description doesn't add any meaningful parameter semantics beyond what's already in the schema (e.g., format examples, validation rules). 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 ('Remove') and target resource ('a task from a project'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this from sibling tools like 'delete_project' or 'update_task', which would require more specific language about scope or permanence.

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 'delete_project' or 'update_task', nor does it mention prerequisites (e.g., task must exist, user permissions). It simply states what the tool does without contextual usage information.

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 the precondition ('all tasks are both done and approved') and workflow context, but lacks details on permissions, side effects, or response format. It adequately describes the core behavior but misses some operational aspects.

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 two sentences with zero waste: the first states the action and precondition, the second provides workflow context. It is front-loaded with the core purpose and appropriately sized 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 the tool's moderate complexity (mutation with a precondition), no annotations, and no output schema, the description is mostly complete. It covers purpose, usage, and behavioral context well, but could benefit from mentioning response format or error conditions to be fully comprehensive.

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 fully documents the single parameter. The description does not add parameter details beyond the schema, but with only one parameter, the baseline is high. It implies the projectId is used to identify the project to finalize.

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 ('Mark a project as complete') and resource ('project'), distinguishing it from siblings like create_project or update_task. It precisely defines the verb and target, making the purpose unambiguous.

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 explicitly states when to use this tool ('when all tasks are both done and approved') and positions it in the workflow ('typically the last step in a project workflow'). It provides clear context for usage without needing to reference alternatives directly.

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 mentions using an LLM and analyzing files, but fails to describe critical traits: it doesn't specify if this is a read-only or mutating operation, what the output format looks like, potential rate limits, error conditions, or costs. For a tool that likely involves external API calls and file processing, this is a significant gap.

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 appropriately concise with two sentences that directly address the tool's function. It's front-loaded with the core purpose and avoids unnecessary details. However, it could be slightly more structured by explicitly separating the tool's action from its inputs or constraints.

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 an LLM-based generation tool with file attachments and no output schema, the description is incomplete. It lacks information on the output format (e.g., structured plan vs. raw text), error handling, dependencies like API keys, and how it integrates with sibling tools. This makes it inadequate for an agent to use effectively without guesswork.

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 thoroughly. The description adds minimal value beyond the schema—it implies that 'attachments' are used as context and that the LLM analyzes the 'prompt', but doesn't provide additional syntax or format details. 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: 'Use an LLM to generate a project plan and tasks from a prompt.' It specifies the verb ('generate'), resource ('project plan and tasks'), and mechanism ('LLM'). However, it doesn't explicitly differentiate from siblings like 'create_project' or 'add_tasks_to_project' beyond the LLM aspect, which is why it doesn't reach 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?

The description provides no guidance on when to use this tool versus alternatives. It mentions analyzing 'prompt and any attached files' but doesn't clarify scenarios where this is preferred over manual creation with 'create_project' or 'add_tasks_to_project', nor does it mention prerequisites like API keys. This leaves the agent with insufficient context for decision-making.

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 discloses that it returns 'the first non-approved task in sequence, regardless of status', which clarifies selection logic beyond a simple read. It also mentions optional fields like toolRecommendations and ruleRecommendations for guidance. However, it doesn't cover error handling, permissions, or response format details, leaving gaps for a mutation-free but context-sensitive 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 two sentences, front-loaded with the core purpose and followed by behavioral details. Every sentence adds value: the first defines the tool's function and selection criteria, and the second explains optional fields for task completion. There is no wasted text 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 no annotations and no output schema, the description is moderately complete. It covers the tool's purpose, selection logic, and optional fields, but lacks details on return values (e.g., task structure), error cases, or dependencies. For a tool with 1 parameter and simple behavior, this is adequate but has clear gaps in fully guiding 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 schema has 1 parameter with 100% description coverage, so the baseline is 3. The description adds value by contextualizing the parameter: it specifies that projectId is used 'to get the next task from', reinforcing its purpose. This goes beyond the schema's generic description, though it doesn't provide additional syntax or format 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' and resource 'next task to be done in a project', specifying it returns 'the first non-approved task in sequence, regardless of status'. This distinguishes it from siblings like list_tasks (which lists all tasks) or read_task (which reads a specific task). However, it doesn't explicitly contrast with all siblings, such as update_task or approve_task, which handle different operations on tasks.

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 when needing the next actionable task in a project, particularly for workflow progression. It mentions 'non-approved task in sequence', suggesting it's for tasks pending approval. However, it lacks explicit guidance on when to use this versus alternatives like list_tasks (for all tasks) or read_task (for a specific task ID), and doesn't specify prerequisites 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?

With no annotations, the description carries full burden but only states it's a list operation. It doesn't disclose behavioral traits like pagination, rate limits, permissions needed, or whether it returns all projects at once. For a list 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?

Single sentence efficiently conveys purpose, output details, and optional filtering. No wasted words, front-loaded with core functionality. Every element 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 simple list tool with 1 parameter and no output schema, the description covers basics but lacks behavioral context. Without annotations or output schema, it should explain return format or limitations more clearly. It's minimally adequate but has gaps.

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 single parameter. The description adds minimal value by mentioning the filtering option but doesn't provide additional semantics beyond what's in the schema. 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 ('projects in the system') with specific output details ('basic information: ID, initial prompt, task counts'). It distinguishes from siblings like 'read_project' (singular detail) and 'list_tasks' (different 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 clear context for when to use it ('list all projects... optionally filtered by state'), but doesn't explicitly state when not to use it or name alternatives. It implies usage vs. 'read_project' for single projects but lacks explicit 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?

With no annotations, the description carries full burden. It discloses that tasks include 'tool and rule recommendations,' which adds behavioral context beyond basic listing. However, it doesn't mention pagination, sorting, rate limits, permissions, or response format. For a list operation with zero annotation coverage, this leaves 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 that front-loads the core functionality (listing tasks with filters) and adds a useful detail about task content. There's no wasted text, but it could be slightly more structured (e.g., separating filtering from content notes).

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 moderately complete for a simple list tool. It covers purpose and filtering, and adds context about task recommendations. However, it lacks details on response structure, error handling, or operational constraints, which are important for an agent to use it effectively without structured output guidance.

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 both parameters. The description adds marginal value by summarizing the filtering options ('optionally filtered by project ID and/or state') and listing state values, but doesn't provide additional syntax, format, or examples beyond what the schema already states. 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 'tasks', specifying optional filtering by project ID and state. It distinguishes from siblings like 'get_next_task' (single task) and 'read_task' (single task by ID), but doesn't explicitly contrast with 'list_projects' or other list operations. The mention of tool/rule recommendations adds useful context about task 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?

The description implies usage through the filtering parameters (project ID, state), suggesting when to apply filters. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_next_task' (for workflow) or 'list_projects' (for project overview). No guidance on prerequisites or exclusions is provided.

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 it reads 'all information' including 'tasks' statuses, which hints at a read-only operation, but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns paginated data, or what happens if the project ID is invalid. For a 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 that front-loads the core action ('read all information') and includes key details (resource, identifier, included data). There is no wasted language, and it effectively communicates the purpose 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 (one parameter, no output schema, no annotations), the description is adequate but not complete. It covers the basic purpose and parameter usage, but lacks details on behavioral aspects like error handling or return format. With no output schema, it should ideally hint at what 'all information' includes, but it does mention tasks' statuses, which adds some 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?

The schema description coverage is 100%, with the parameter 'projectId' well-documented in the schema. The description adds minimal value beyond the schema by mentioning 'by its ID', but doesn't provide additional context like format examples or constraints. 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 verb ('read') and resource ('project'), specifying it retrieves 'all information' including 'tasks' statuses. It distinguishes from siblings like 'list_projects' (which lists multiple) and 'read_task' (which reads a single task), though not explicitly. However, it doesn't fully differentiate from potential overlaps like 'get_next_task' or 'generate_project_plan' in terms of 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?

The description implies usage by stating 'by its ID', suggesting it's for reading a specific project rather than listing all. However, it doesn't explicitly state when to use this versus alternatives like 'list_projects' for overviews or 'read_task' for task details, nor does it mention prerequisites or exclusions. The guidance is present but not 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool retrieves details and notes specific fields (toolRecommendations, ruleRecommendations), but lacks critical information such as whether this is a read-only operation, error handling for invalid IDs, or any rate limits. This leaves gaps in understanding the tool's behavior beyond basic functionality.

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 highly concise and well-structured in two sentences: the first states the core purpose, and the second adds valuable context about specific fields. Every sentence earns its place by providing essential information 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 the tool's moderate complexity (2 required parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the purpose and hints at usage through field mentions, but lacks details on behavioral aspects like error cases or output structure, which are important for a read operation in a task management 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?

The input schema has 100% description coverage, clearly documenting both parameters (projectId and taskId) with examples. The description doesn't add any additional semantic information about the parameters beyond what the schema provides, such as format constraints or relationships between projectId and taskId, so it 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 with a specific verb ('Get details') and resource ('a specific task by its ID'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate itself from sibling tools like 'list_tasks' or 'read_project', which would be needed for 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 implies usage by mentioning that the task includes 'toolRecommendations and ruleRecommendations fields that should be used to guide task completion,' suggesting this tool is for retrieving task details to inform actions. However, it doesn't provide explicit guidance on when to use this versus alternatives like 'list_tasks' for overviews or 'get_next_task' for workflow sequencing.

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 and does well by disclosing key behavioral traits: required conditions for 'completedDetails', restrictions on approved tasks, and valid status transitions. It doesn't cover aspects like error handling or response format, but adds substantial value beyond basic functionality.

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 appropriately sized and front-loaded with the core purpose, followed by specific notes. Each sentence adds value (e.g., constraints and additional capabilities), though it could be slightly more streamlined by integrating the recommendation update into the opening statement.

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 an update tool with 8 parameters, no annotations, and no output schema, the description is adequate but has gaps. It covers key behavioral rules and some parameter context, but lacks details on error cases, response format, or broader system implications, making it minimally viable rather than comprehensive.

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 thoroughly. The description adds minimal semantic context (e.g., linking 'completedDetails' to 'done' status and mentioning updates to recommendations), but doesn't significantly enhance understanding beyond the schema, justifying the baseline score.

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 ('Modify') and resource ('task's properties'), making the purpose evident. However, it doesn't explicitly differentiate from sibling tools like 'create_task' or 'delete_task' beyond the basic action, 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 clear context on when to use this tool (e.g., to update task properties) and includes important constraints like 'approved tasks cannot be modified' and status transition rules. It doesn't explicitly name alternatives like 'create_task' for new tasks or mention prerequisites, keeping it from a 5.

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