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 but doesn't mention whether this requires admin permissions, what happens if the user is already a collaborator, rate limits, or the response format. This leaves significant 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 with zero wasted words. It's appropriately sized and front-loaded with the core action, 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 that this is a mutation tool with no annotations but has an output schema (which handles return values), the description is minimally adequate. However, it lacks important context about permissions, error conditions, and behavioral nuances that would be helpful for 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?

Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, meeting the baseline score 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 action ('Add') and target ('a collaborator to a repository'), providing a specific verb+resource combination. However, it doesn't differentiate from the sibling 'remove_collaborator' tool, which would require explicit comparison to achieve a score of 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 like 'list_collaborators' or 'remove_collaborator', nor does it mention prerequisites such as required permissions or repository ownership. It lacks explicit context for usage decisions.

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 ('Cancel') which implies a destructive mutation, but provides no information about permissions required, whether cancellation is reversible, what happens to the workflow run, error conditions, or rate limits. 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 extremely concise - a single sentence with zero wasted words. It's front-loaded with the essential action and target, making it 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?

For a mutation tool with no annotations and significant behavioral implications, the description is insufficiently complete. While there's an output schema (which reduces need to describe return values), the description lacks critical context about permissions, side effects, error conditions, and usage constraints that would help an agent use this tool 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?

The input schema has 100% description coverage, with all three parameters clearly documented in the schema itself. The description adds no additional parameter information beyond what's in the schema, so the baseline score 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 action ('Cancel') and target resource ('a workflow run'), making the purpose immediately understandable. It doesn't distinguish from siblings like 'list_workflow_runs' or 'trigger_workflow', but the verb+resource combination is specific enough for basic understanding.

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, prerequisites, or constraints. The description offers no context about workflow state requirements, permissions needed, or what happens after cancellation compared to other workflow-related 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 creation but fails to describe key traits like whether this requires write permissions, if the branch is created from a specific commit or default branch, error conditions (e.g., duplicate branch names), or the response format. This leaves significant gaps for an AI agent.

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, front-loading the core action. It is appropriately sized for the tool's complexity, 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?

Given the tool's moderate complexity (4 parameters, mutation operation) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete behavioral context, it lacks details on permissions, error handling, or sibling differentiation, making it only partially complete 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 clear descriptions for all parameters (e.g., 'Repository owner', 'Name for the new branch'). The description adds no additional meaning beyond the schema, such as explaining parameter interactions or constraints, so it meets the baseline for high schema coverage without enhancing parameter understanding.

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 branch in a repository'), making the purpose immediately understandable. It distinguishes from siblings like 'delete_branch' or 'list_branches' by specifying creation. However, it lacks specificity about what kind of repository (e.g., Git) or any constraints, 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 'fork_repository' or 'create_pull_request', nor does it mention prerequisites such as repository access or 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 full burden but only states the basic action without disclosing behavioral traits. It doesn't mention whether this is a write operation, what permissions are needed, if it's idempotent, or what happens on failure. This leaves significant 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 extremely concise with just one sentence that directly states the tool's purpose. There's no wasted language or unnecessary elaboration, making it efficiently front-loaded.

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 7 parameters and no annotations, the description is minimal but not completely inadequate due to the existence of an output schema. However, it should provide more context about the operation's nature and typical use cases given the complexity.

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 7 parameters. The description adds no additional parameter information beyond implying 'sha' is required, which is already in the schema. 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 ('commit status for a specific SHA'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'list_commit_statuses' or explain what a commit status is, 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?

No guidance is provided on when to use this tool versus alternatives like 'update_issue' for status tracking or 'list_commit_statuses' for checking existing statuses. The description lacks context about prerequisites 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?

No annotations are provided, so the description carries full burden. 'Create a new gist' implies a write operation, but it doesn't disclose behavioral traits like authentication requirements, rate limits, whether the gist is immediately available, or what happens on failure. 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 with the core action and resource, 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 that there's an output schema (which handles return values), no annotations, and 100% schema coverage, the description is minimally adequate. However, for a creation tool with no annotations, it should ideally provide more behavioral context (e.g., permissions, side effects) to be fully complete.

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 no parameter semantics beyond what's in the schema, maintaining the baseline score of 3 where 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 ('Create') and resource ('new gist'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'update_gist' or 'get_gist', but the action is specific enough to be 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 provides no guidance on when to use this tool versus alternatives like 'update_gist' or 'get_gist', nor does it mention prerequisites or context for creation. It's a bare statement of function without 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. While 'Create' implies a write operation, the description doesn't mention required permissions, rate limits, whether the issue is public/private, or what happens on success/failure. For a mutation tool with zero 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 extremely concise with just one sentence that directly states the tool's purpose. There's zero wasted language, and it's front-loaded with 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 that this is a mutation tool with no annotations but has a rich input schema (100% coverage) and an output schema exists, the description is minimally adequate. However, it should do more to compensate for the lack of annotations by explaining behavioral aspects like permissions or error handling, making it incomplete for safe 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 documents all 6 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema (e.g., it doesn't explain relationships between parameters or provide examples). 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 ('Create') and resource ('new issue in a repository'), making the purpose immediately understandable. However, it doesn't differentiate this tool from similar sibling tools like 'create_pull_request' or 'create_label', which would require specifying that this creates specifically an issue (not a PR, label, etc.).

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., authentication, repository access), when not to use it (e.g., for creating pull requests instead), or refer to related tools like 'update_issue' or 'list_issues' for 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. It states the action ('Add a comment') but doesn't cover critical traits: it doesn't clarify that this is a mutation (creating new data), mention authentication needs, rate limits, or what the output contains. For a write operation 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 extremely concise and front-loaded: 'Add a comment to an issue.' It uses a single, direct sentence with zero waste, making it easy to parse. Every word earns its place by clearly stating the core action 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 the tool's moderate complexity (a write operation with 4 parameters) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and incomplete behavioral context, it leaves gaps in understanding permissions, side effects, and usage guidelines. It meets the bare minimum but could be more informative.

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 four parameters (owner, repo, issue_number, body). The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. Given the 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 tool's purpose: 'Add a comment to an issue.' It specifies the verb ('Add') and resource ('comment to an issue'), making it understandable. However, it doesn't differentiate from sibling tools like 'create_review_comment' or 'reply_to_review_comment', which are related but distinct comment-creation tools in the same GitHub 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 issue), exclusions, or comparisons to siblings like 'create_review_comment' (for pull request reviews) or 'reply_to_review_comment'. 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action without mentioning permissions required, whether the operation is idempotent, error conditions (e.g., duplicate labels), rate limits, or what the output contains. 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 extremely concise with just one sentence, front-loading the core purpose without any wasted words. It's appropriately sized for a simple tool, though this conciseness comes at the cost of completeness 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 this is a mutation tool with no annotations, 5 parameters, and an output schema (which helps), the description is incomplete. It lacks behavioral context (permissions, errors), usage guidance, and doesn't compensate for the absence of annotations. The output schema existence prevents the lowest score, but the description alone is insufficient.

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 5 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema, such as format examples or constraints. 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 clearly states the action ('Create') and resource ('a label in a repository'), making the purpose understandable. It distinguishes from siblings like 'delete_label' or 'list_labels' by specifying creation, but doesn't explicitly differentiate from other creation tools like 'create_issue' or 'create_repository' 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. It doesn't mention prerequisites (e.g., repository access), when not to use it (e.g., if label already exists), or suggest related tools like 'list_labels' for checking existing labels before creation.

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 updates require a SHA and creation does not, which is useful behavioral context. However, it does not mention permissions needed, rate limits, commit effects, or error handling, leaving gaps for a mutation tool with no 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 two sentences with zero waste, front-loaded with the core purpose and followed by a critical usage note. Every word serves a clear function, making it highly 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 tool's complexity (mutation with 7 parameters) and no annotations, the description is somewhat complete but lacks details on permissions, side effects, or error cases. However, the presence of an output schema reduces the need to explain return values, and the description covers the key behavioral distinction between create and update operations.

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%, providing full parameter documentation. The description adds minimal value beyond the schema by implying the dual use of 'sha' for updates versus creation, but does not elaborate on parameter interactions or constraints beyond what's already in the schema descriptions.

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 ('create or update a file in a repository') and resource ('file'), distinguishing it from siblings like 'delete_file', 'get_file_contents', or 'push_files'. It precisely defines the dual functionality in a concise manner.

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 the update functionality ('you must provide the current file's SHA'), but does not explicitly mention when to use this tool versus alternatives like 'push_files' or 'create_repository' for broader operations. It offers some guidance but lacks explicit exclusions or sibling comparisons.

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. It states the action but doesn't describe what 'create a review' entails operationally - whether this submits a final review, requires specific permissions, affects PR status, or has side effects. The description doesn't mention the event parameter's significance or the body requirement for certain events.

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 two sentences with zero wasted words. It's front-loaded with the core purpose and doesn't include unnecessary elaboration. Every word serves a clear purpose in communicating 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 tool's moderate complexity (5 parameters, mutation operation) and the presence of an output schema, the description is minimally adequate but lacks important context. It doesn't explain the review creation workflow, how this differs from commenting, or what permissions are required. The output schema existence means return values are documented elsewhere, but the description should still provide more operational 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 baseline is 3. The description doesn't add meaningful parameter context beyond what's already documented in the schema - it doesn't explain relationships between parameters (like how 'event' determines 'body' requirements) or provide usage examples. The schema already documents all parameters 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 action ('Create a review') and target resource ('on a pull request'), providing a specific verb+resource combination. However, it doesn't distinguish this from the sibling 'create_review_comment' tool, which appears to serve a related but different function.

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 like 'create_review_comment' or 'update_pull_request'. There's no mention of prerequisites, appropriate contexts, or exclusions for this review creation operation.

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 'create' implies a write operation, the description doesn't mention authentication requirements, rate limits, whether it's idempotent, what happens on conflicts, or the response format. 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 extremely concise with just two words, making it front-loaded and efficient. There's no wasted language or unnecessary elaboration, though this brevity comes at the cost of completeness 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 the tool's complexity (a mutation operation with 7 parameters) and the presence of an output schema (which reduces the need to describe return values), the description is minimally adequate. However, with no annotations and many sibling tools, it lacks sufficient context about usage scenarios and behavioral traits to be fully complete.

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 7 parameters thoroughly. The description adds no additional parameter information beyond what's in the schema, which meets the baseline expectation when the schema does the heavy lifting, but doesn't provide 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 states the verb ('create') and resource ('pull request'), making the basic purpose clear. However, it doesn't differentiate this from similar tools like 'create_issue' or 'merge_pull_request' among the many sibling tools, leaving ambiguity about when to use this specific creation tool versus 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 'create_issue', 'merge_pull_request', and 'update_pull_request', there's no indication of prerequisites, appropriate contexts, or exclusions to help an agent choose correctly.

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 action ('Create') but doesn't describe what happens upon execution—such as whether it requires specific permissions, if it's idempotent, what the typical response includes, 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 extremely concise—just two words—and front-loaded with the core action. There is zero wasted language, making it efficient for quick comprehension. However, this conciseness comes at the cost of completeness, as noted 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 the complexity (a mutation tool with 9 parameters) and the presence of an output schema (which reduces the need to describe return values), the description is incomplete. It lacks behavioral context, usage guidelines, and any mention of the tool's scope or constraints. While the output schema may cover response structure, the description doesn't prepare the agent for execution nuances, making it inadequate for a tool of this nature.

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 input schema (e.g., 'tag_name' as 'Tag name for the release'). The description adds no additional parameter semantics beyond the schema, so it meets the baseline of 3 where the schema does the heavy lifting. No parameters are explained in the description text itself.

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 ('Create') and resource ('a new release'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'get_latest_release' or 'list_releases' by specifying creation rather than retrieval. However, it doesn't explicitly differentiate from other creation tools like 'create_issue' or 'create_pull_request' 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., repository access), when not to use it (e.g., for updating releases), or refer to sibling tools like 'get_release_by_tag' for checking existing releases. 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 mentions the user context but lacks critical behavioral details: required permissions, rate limits, whether creation is irreversible, or what happens on failure. 'Create' implies a mutation, but no safety or operational context is given.

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 and efficiently includes the user context, making it 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 tool's complexity (mutation with 4 parameters), no annotations, but with a complete input schema and an output schema (implied by context signals), the description is minimally adequate. It covers the basic purpose but lacks behavioral transparency and usage guidance, leaving gaps for 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 4 parameters (name, description, private, auto_init). The description adds no parameter-specific information beyond what's in the schema, 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 action ('Create') and resource ('new repository'), specifying it's for the authenticated user. It distinguishes from siblings like 'fork_repository' (which creates a fork) and 'list_repositories' (which lists), but doesn't explicitly contrast with other creation tools like 'create_gist' or 'create_issue'.

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, stating it's for the authenticated user but not when to use it versus alternatives like 'fork_repository' or prerequisites. No explicit when-not-to-use or comparison with sibling creation tools is included.

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 creates a comment, implying a write operation, but does not disclose any behavioral traits such as required permissions, whether the comment is editable/deletable, rate limits, or how it integrates with GitHub's review workflow. This leaves significant gaps for an agent to understand the tool's 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, clear sentence that directly states the tool's purpose without any unnecessary words. It is front-loaded and efficiently conveys the core action, making it easy for an agent to quickly understand 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?

Given the complexity of 11 parameters (6 required) and no annotations, the description is minimal but adequate as a starting point. However, it lacks details on behavioral aspects like permissions or workflow integration. The presence of an output schema means the description does not need to explain return values, but it could benefit from more context to fully guide usage in a GitHub review scenario.

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 each parameter well-documented in the schema itself (e.g., 'owner' as 'Repository owner', 'line' as 'The line number in the diff to comment on'). The description adds no additional meaning beyond the schema, such as explaining parameter interactions or constraints, so it meets the baseline score of 3 where 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 ('Create a review comment') and the target ('on a specific line of a pull request diff'), which is a specific verb+resource combination. However, it does not explicitly distinguish this tool from sibling tools like 'create_issue_comment' or 'create_pr_review', which are related but serve different purposes in GitHub's review system.

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 sibling tools like 'create_issue_comment' (for general issue comments) or 'create_pr_review' (for overall PR reviews), nor does it specify prerequisites or exclusions, such as requiring review permissions or being applicable only during code review processes.

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 ('Create') but provides no information about permissions required, rate limits, whether the operation is idempotent, what happens on duplicate webhooks, or what the response contains. 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 extremely concise - a single sentence that states the core purpose without any wasted words. It's front-loaded with the essential information and contains no unnecessary elaboration 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 that this is a mutation tool with 7 parameters, no annotations, but with complete schema coverage and an output schema, the description is minimally adequate. The output schema reduces the need to describe return values, but the description should still address behavioral aspects like permissions, side effects, and usage context that aren't captured in structured fields.

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 7 parameters thoroughly. The description adds no parameter information beyond what's in the schema. This meets the baseline expectation when schema coverage is complete, but doesn't provide additional context about parameter interactions or usage patterns.

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 ('a webhook for a repository'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'list_webhooks' or 'delete_webhook', but the verb 'Create' provides sufficient distinction for basic understanding.

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 (like repository access), when webhooks are appropriate versus polling, or how it differs from related tools like 'list_webhooks' or 'delete_webhook' in the sibling list.

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 lacks critical behavioral details. It doesn't mention permissions required, whether deletion is irreversible, rate limits, or error conditions. 'Delete' implies a destructive mutation, 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, direct sentence with zero waste, efficiently conveying the core purpose. 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 this is a destructive mutation tool with no annotations, the description is incomplete. It lacks behavioral context, usage guidance, and output details, though an output schema exists. For a tool that permanently removes data, more disclosure 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 all parameters clearly documented in the schema. The description adds no additional meaning beyond the schema, such as format examples or constraints. Baseline 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 clearly states the action ('Delete') and target resource ('a branch from a repository'), providing a specific verb+resource combination. However, it doesn't differentiate from sibling tools like 'delete_file' or 'delete_label' beyond the obvious resource difference, missing explicit comparison.

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 'delete_branch_protection' or 'create_branch', nor any prerequisites or exclusions. The description only states what it does 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Delete') which implies a destructive mutation, but doesn't mention permissions required, irreversible consequences, rate limits, or what the output looks like. 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 a single, direct sentence with no wasted words. It's front-loaded with the core action and resource, making it highly 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?

For a destructive mutation tool with no annotations, the description is incomplete. It lacks critical context like required permissions, irreversible effects, or error conditions. While an output schema exists (which helps), the description doesn't compensate for the missing behavioral transparency needed for safe tool 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 (owner, repo, branch) clearly documented in the schema. The description adds no additional parameter details beyond what the schema provides, so it meets the baseline 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 ('Delete') and resource ('branch protection rules for a branch'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'delete_branch' or 'update_branch_protection', 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 (e.g., 'update_branch_protection' for modifying rules, 'delete_branch' for removing the branch itself) or any prerequisites. The description only states what it does, not when it's appropriate.

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 destructive action ('Delete') but doesn't mention important behavioral aspects: that this is irreversible, requires appropriate permissions, creates a commit (implied by the message parameter but not stated), or what happens on failure. The description is minimal and lacks crucial context 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 - a single sentence with zero wasted words. It's front-loaded with the core purpose and contains no unnecessary information. This is an example of efficient communication, though the brevity comes at the cost of completeness.

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 but with an output schema, the description is inadequate. It doesn't explain the commit behavior, permission requirements, error conditions, or relationship to other tools. While the output schema may document return values, the description fails to provide crucial operational context for a high-risk operation.

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 6 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema - it doesn't explain parameter relationships, constraints, or usage patterns. Baseline 3 is appropriate when the schema does all the parameter documentation 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 ('Delete') and resource ('a file from a repository'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling deletion tools like delete_branch, delete_label, or delete_webhook, which all delete different resources in the same repository 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 (like needing the file's SHA from get_file_contents, which is only hinted in the schema), when deletion is appropriate versus modification, or how this differs from other deletion tools in the sibling list.

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 the action ('Delete') but does not disclose behavioral traits such as whether deletion is permanent, requires specific permissions, or has side effects (e.g., affecting issues with that label). This leaves significant gaps 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 a single, efficient sentence with zero waste. It is front-loaded and directly states the tool's purpose without unnecessary elaboration, 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 that this is a destructive tool with no annotations, the description is minimal and lacks important context like safety warnings or output details. However, an output schema exists (per context signals), so the description does not need to explain return values. It is adequate but has clear gaps in behavioral transparency.

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 (owner, repo, name) with clear descriptions. The description does not add any meaning beyond what the schema provides, such as explaining parameter relationships or constraints, but this is acceptable given the high schema coverage, resulting in a baseline score of 3.

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 ('Delete') and resource ('a label from a repository'), making the purpose unambiguous. However, it does not differentiate from sibling tools like 'delete_branch' or 'delete_file', which follow the same pattern but target different resources, so it lacks explicit sibling 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. For example, it does not mention prerequisites (e.g., needing admin permissions) or compare with related tools like 'list_labels' for verification. The description only states the action without 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 full burden for behavioral disclosure. It states the action is 'Delete' which implies a destructive mutation, but doesn't clarify permissions required, whether deletion is permanent/reversible, rate limits, or what the output contains. 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 a single, clear 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.

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, the description is minimally adequate but incomplete. The presence of an output schema reduces the need to describe return values, but the description lacks crucial behavioral context about permissions, consequences, and relationships to other tools. It's borderline viable but has clear 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 all three parameters (owner, repo, hook_id) with their purposes. The description adds no additional parameter context beyond implying these are needed to identify the webhook. 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 ('Delete') and resource ('a webhook from a repository'), making the purpose immediately understandable. However, it doesn't differentiate this tool from sibling deletion tools like delete_branch or delete_label, which would require specifying the resource type more distinctly.

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 webhook), when not to use it, or how it relates to sibling tools like list_webhooks or create_webhook. This leaves the agent without context for proper 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?

No annotations are provided, so the description carries full burden. It states the action ('Fork') but doesn't disclose behavioral traits such as whether this requires write permissions, if it's idempotent, what happens on success/failure, rate limits, or the effect on the original repository. The description is too sparse for a mutation tool with no 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 extremely concise with just two words, front-loading the key action. There is no wasted language, making it efficient, though this brevity 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 that there's an output schema (which handles return values) and full schema coverage for parameters, the description doesn't need to explain those. However, for a mutation tool with no annotations, it should provide more behavioral context (e.g., permissions, side effects). The description is minimally complete but lacks depth 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%, so the schema already documents all parameters (owner, repo, organization) with descriptions. The description adds no additional meaning beyond the schema, such as explaining the relationship between parameters or usage examples. 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 states the action ('Fork') and resource ('a repository'), which is clear but minimal. It doesn't differentiate from sibling tools like 'create_repository' or explain what forking entails (e.g., creating a copy under user's account vs. organization). The description is adequate but lacks specificity about scope or outcome.

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., authentication, permissions), when forking is appropriate compared to cloning or creating a new repository, or how it relates to sibling tools like 'create_repository'. The description 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?

With no annotations provided, the description carries full burden but only states what the tool does, not behavioral traits. It doesn't mention authentication requirements, rate limits, response format, or whether this is a read-only operation. For a tool with zero annotation coverage, this is insufficient disclosure.

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 purpose and efficiently communicates the essential information 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 the tool has an output schema (which handles return values) and 100% parameter schema coverage, the description is minimally adequate. However, with no annotations and a sibling tool ('get_user') that serves a similar purpose, more guidance on when to use this specific tool would improve 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, so the schema fully documents the empty parameter set. The description appropriately doesn't add parameter information beyond what's already covered, earning a baseline score of 4 for zero-parameter tools.

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 currently authenticated user', making the purpose unambiguous. It doesn't explicitly differentiate from sibling 'get_user', but the distinction is implied through 'currently authenticated' vs. general user lookup.

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 ('currently authenticated user') but doesn't explicitly state when to use this vs. the sibling 'get_user' tool. No alternative tools or exclusions are mentioned, leaving some ambiguity about 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 the full burden of behavioral disclosure but offers minimal information. It states the action ('Get') but doesn't describe the tool's behavior—such as what permissions are required, whether it's idempotent, how errors are handled, or the format of the returned protection rules. For a read operation with zero annotation coverage, this leaves significant gaps in understanding how the tool behaves in practice.

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—a single sentence that directly states the tool's purpose without any fluff or redundant information. It's front-loaded and wastes no words, making it easy to parse quickly. Every part of the sentence earns its place by clearly communicating 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?

Given the tool's moderate complexity (a read operation with three required parameters), the description is minimally complete. The presence of an output schema means the description doesn't need to explain return values, but it lacks context on authentication, error handling, or usage scenarios. With no annotations and a basic description, it meets the minimum threshold but leaves the agent to rely heavily on the structured fields for full 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?

The description adds no parameter-specific information beyond what's already in the input schema, which has 100% coverage with clear descriptions for 'owner', 'repo', and 'branch'. Since the schema fully documents the parameters, the baseline score of 3 is appropriate—the description doesn't compensate but also doesn't need to, as the schema provides adequate 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 tool's purpose with a specific verb ('Get') and resource ('branch protection rules for a branch'), making it immediately understandable. It distinguishes from siblings like 'update_branch_protection' and 'delete_branch_protection' by focusing on retrieval rather than modification. However, it doesn't explicitly differentiate from other read operations like 'list_branches' beyond the specific 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. It doesn't mention prerequisites (e.g., authentication requirements), when not to use it, or how it differs from related tools like 'list_branches' or 'get_repository' that might provide overlapping information. 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 it's a read operation ('Get'), which implies safety, but doesn't cover authentication needs, rate limits, error handling, or what the output contains. This leaves significant gaps for a tool that likely interacts with an API.

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 zero wasted words. It's front-loaded with the core action and resource, making it highly efficient and 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 simplicity (a basic read operation), 100% schema coverage, and the presence of an output schema, the description is minimally adequate. However, with no annotations and lacking behavioral details, it doesn't fully prepare the agent for real-world usage, such as authentication or error scenarios.

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 three required parameters (owner, repo, check_run_id). The description adds no additional semantic context beyond implying an ID lookup, so it meets the baseline score without compensating for any 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 action ('Get') and resource ('a single check run by ID'), making the purpose specific and understandable. However, it doesn't differentiate from sibling tools like 'list_check_runs' or explain what a 'check run' is in this 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 like 'list_check_runs' or other retrieval tools. There's no mention of prerequisites, error conditions, or typical use cases, leaving the agent with minimal contextual 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 the full burden. It mentions what details are retrieved but doesn't disclose behavioral traits such as authentication requirements, rate limits, error conditions, or response format. For a read operation with no annotation coverage, 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, efficient sentence with zero waste. It is appropriately sized and front-loaded, clearly stating the tool's 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?

Given the tool's low complexity (a simple read operation), 100% schema coverage, and the presence of an output schema (which handles return values), the description is mostly complete. However, it lacks behavioral context that annotations would typically provide, such as safety or performance hints.

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 (owner, repo, ref). The description adds no additional meaning beyond what the schema provides, such as examples or constraints. 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 with a specific verb ('Get details') and resource ('a specific commit'), including what details are retrieved ('stats and changed files'). It distinguishes from siblings like 'list_commits' by focusing on a single commit, but doesn't explicitly mention this 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 like 'list_commits' or 'get_repository_tree'. The description implies usage for retrieving details of a specific commit, but lacks explicit context, 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool gets details but doesn't specify what 'details' include (e.g., metadata, content, participants), whether it's a read-only operation, any rate limits, authentication needs, or error conditions. This leaves significant gaps in understanding the tool's behavior beyond basic purpose.

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 sentence: 'Get details of a specific discussion.' It is front-loaded and wastes no words, making it easy to parse quickly. Every part of the sentence contributes directly to understanding the tool's 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?

Given the tool's moderate complexity (fetching a specific resource), the presence of an output schema reduces the need to describe return values in the description. However, with no annotations and incomplete behavioral transparency, the description lacks context on usage scenarios, error handling, and differentiation from siblings. It's minimally adequate but has clear gaps in providing a complete picture for effective 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?

The input schema has 100% description coverage, with clear documentation for 'owner,' 'repo,' and 'number' parameters. The description adds no additional semantic context beyond what the schema provides, such as explaining parameter relationships or usage examples. Given the high schema coverage, the 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 clearly states the tool's purpose: 'Get details of a specific discussion.' It uses a specific verb ('Get') and resource ('discussion'), making it easy to understand. However, it doesn't distinguish this tool from its sibling 'get_discussion_comments,' which could cause confusion about which to use for retrieving discussion content versus comments.

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 like 'list_discussions' (for listing discussions) and 'get_discussion_comments' (for retrieving comments), the agent lacks explicit instructions on when this tool is appropriate, such as for fetching metadata or full discussion content versus other related 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the action is to 'get' comments, implying a read-only operation, but doesn't clarify pagination behavior (the 'first' parameter suggests it returns a subset), rate limits, authentication needs, or error conditions. This leaves significant gaps for an agent to understand how to use it effectively.

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—a single sentence with no wasted words. It's front-loaded with the core purpose, though this brevity comes at the cost of completeness. Every word earns its place by stating the essential action.

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 (4 parameters, no annotations, but with an output schema), the description is minimally adequate. The output schema likely covers return values, reducing the need for description details. However, the lack of behavioral context and usage guidelines leaves gaps that could hinder an agent's ability to select and invoke the tool correctly in varied scenarios.

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 parameters (owner, repo, number, first). The description adds no additional semantic context beyond implying a discussion context, which is already covered by the parameter names and schema descriptions. 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 states the tool's purpose as 'Get comments on a discussion,' which is a clear verb+resource combination. However, it doesn't differentiate from sibling tools like 'list_issue_comments' or 'list_review_comments,' leaving ambiguity about what type of discussion this refers to (e.g., GitHub Discussions vs. other 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. It doesn't mention prerequisites (e.g., needing a discussion number), exclusions, or how it differs from similar tools like 'get_discussion' or 'list_discussions,' which are present in the sibling list.

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 adds some behavioral context: it specifies that the tool returns JSON with a 'type' field for consistent parsing, which helps understand the output structure. However, it lacks details on error handling, rate limits, authentication needs, or whether it's a read-only operation (though 'Get' implies reading). For a tool with no annotations, this is a moderate but incomplete disclosure.

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 very concise and well-structured: two sentences that directly state the purpose and output format, with no wasted words. It's front-loaded with the core functionality, making it easy to parse quickly. Every sentence adds value 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 context: no annotations, 4 parameters with full schema coverage, and an output schema (implied by 'Returns JSON'), the description is reasonably complete. It covers the basic purpose and output structure, which is sufficient for a read operation. However, it could be more complete by addressing authentication or error scenarios, but the output schema likely handles return values, so this isn't critical.

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 the schema already documents all parameters (owner, repo, path, ref) thoroughly. The description doesn't add any parameter-specific details beyond what's in the schema, such as examples or edge cases. According to the rules, with high schema coverage, the baseline is 3, which is appropriate here as the description doesn't compensate but doesn't need to.

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: 'Get the contents of a file or directory listing in a repository.' This specifies the verb ('Get') and resource ('contents of a file or directory listing'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'get_repository_tree' or 'get_gist', which might have overlapping functionality in a GitHub 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. With many sibling tools like 'get_repository_tree', 'get_gist', and 'get_file' (implied by context), there's no indication of specific use cases, prerequisites, or exclusions. This leaves the agent to infer usage based on 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 the tool retrieves a gist and its contents, which implies a read-only operation, but doesn't clarify aspects like authentication needs, rate limits, error handling, or the response format. 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 extremely concise—a single sentence that directly states the tool's purpose without any fluff. It's front-loaded with the core action, making it efficient and easy to parse, though it could benefit from more detail for completeness.

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, read-only operation) and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks behavioral context like authentication or error handling, and with no annotations, it doesn't fully compensate for these gaps, making it only partially complete.

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 'gist_id' clearly documented. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints. According to the rules, this baseline score 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 verb ('Get') and resource ('a specific gist with its file contents'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_gists' or 'update_gist', which would require mentioning it retrieves a single gist by ID rather than listing or modifying.

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 like 'list_gists' for browsing gists or 'update_gist' for modifications, nor does it specify prerequisites such as needing the gist ID or authentication 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states that it retrieves 'detailed information' without specifying what that includes, whether it's a read-only operation, or any authentication requirements. For a tool with no annotations, 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 extremely concise—just one sentence—and front-loaded with the core purpose. There is no wasted language, making it efficient for an agent 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 that there is an output schema (which handles return values) and 100% schema coverage for inputs, the description's minimalism is somewhat acceptable. However, with no annotations and sibling tools present, it lacks context on usage and behavior, making it incomplete for optimal agent decision-making.

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 the parameters beyond what the schema provides (e.g., it doesn't clarify the relationship between owner, repo, and issue_number). 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: 'Get detailed information about a specific issue.' It uses a specific verb ('Get') and resource ('issue'), making it easy to understand. However, it doesn't differentiate from sibling tools like 'list_issues' or 'search_issues', 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. With sibling tools like 'list_issues' and 'search_issues' available, the agent receives no help in choosing between retrieving a single known issue versus listing or searching for multiple issues.

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 the action but doesn't disclose behavioral traits such as whether this is a read-only operation, what happens if no release exists, rate limits, authentication needs, or the response format. This is inadequate for a 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 no wasted words. It's front-loaded with the core purpose, making it easy to scan and understand 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 low complexity (2 simple parameters) and the presence of an output schema (which handles return values), the description is minimally adequate. However, with no annotations and no guidance on usage versus siblings, it lacks completeness for effective agent decision-making.

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 (owner and repo). The description adds no additional meaning beyond what the schema provides, such as format examples or constraints, so it 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 ('Get') and resource ('latest published release of a repository'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'get_release_by_tag' or 'list_releases', which offer related functionality for releases.

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_release_by_tag' or 'list_releases'. The description lacks context about use cases, prerequisites, 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 full burden for behavioral disclosure. It states the tool retrieves 'detailed information' but doesn't specify what details are included (e.g., metadata, members, settings), whether it requires authentication, rate limits, or error conditions. This leaves significant gaps for a tool that likely interacts with organizational data.

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 states the tool's purpose without unnecessary words. It's appropriately sized for a simple retrieval tool, though it could be slightly more informative without losing conciseness. The structure is front-loaded with the core action.

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, read-only operation implied by 'get'), the presence of an output schema (which handles return values), and high schema coverage, the description is minimally adequate. However, it lacks behavioral context (e.g., authentication needs, error handling) that would be helpful despite the output schema, especially with no annotations provided.

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 'org' documented as 'Organization name'. The description adds no additional parameter semantics beyond what the schema provides (e.g., format examples, validation rules, or how to specify the organization). 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 tool's purpose with a specific verb ('Get') and resource ('detailed information about an organization'). It distinguishes from siblings like 'get_user' or 'get_repository' by focusing on organizations. However, it doesn't explicitly differentiate from potential sibling 'list_user_orgs' which might list organizations rather than get details about a specific one.

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., authentication needs), when not to use it, or how it differs from related tools like 'list_user_orgs' or 'get_authenticated_user' in the sibling list. 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. While 'Get details' implies a read-only operation, the description doesn't specify authentication requirements, rate limits, error conditions, or what 'details' include. 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, clear sentence that efficiently states the tool's purpose without unnecessary words. It's appropriately sized for a simple retrieval tool, though it could be slightly more informative without sacrificing 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 that there's an output schema (which handles return values) and 100% schema description coverage, the description is minimally adequate. However, for a tool with no annotations and multiple sibling tools, it should provide more context about when to use it and what 'details' means. The completeness is borderline acceptable.

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 documents all three parameters (owner, project_number, owner_type) with their descriptions and types. The description adds no additional parameter information beyond what the schema provides, maintaining the baseline score of 3.

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 'Get details of a specific Project V2' which clearly indicates a retrieval operation on a specific resource. However, it doesn't distinguish this from sibling tools like 'list_projects_v2' or 'list_project_v2_items' which might retrieve multiple projects or project items. 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 when to use 'get_project_v2' versus 'list_projects_v2' or other project-related tools, nor does it specify any prerequisites or contextual constraints 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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed information' but doesn't specify what that includes (e.g., metadata, comments, files), whether it requires authentication, rate limits, or error conditions. This leaves significant gaps in understanding how the tool behaves 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, clear sentence that efficiently states the tool's purpose without unnecessary words. It's appropriately sized for a simple retrieval tool, though it could be slightly more informative without losing 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 moderate complexity (retrieving detailed PR data), the presence of an output schema reduces the need to describe return values in the description. However, with no annotations and minimal behavioral context, the description is adequate but leaves gaps in understanding usage scenarios and behavioral traits, making it just sufficient for basic 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 three parameters (owner, repo, pull_number). The description doesn't add any parameter-specific details beyond what the schema provides, so it meets the baseline score of 3 where 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 ('Get') and resource ('detailed information about a pull request'), making it easy to understand what the tool does. However, it doesn't differentiate from sibling tools like 'get_issue' or 'list_pull_requests' beyond the obvious resource difference, 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. With siblings like 'list_pull_requests' (for listing multiple PRs) and 'get_issue' (for similar detailed retrieval of issues), there's no indication of when this specific retrieval tool is preferred or what distinguishes it contextually.

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 action ('Get') but doesn't describe traits like authentication requirements, rate limits, error handling, or response format. For a read operation in a GitHub context, this omission is significant, though not contradictory.

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 and front-loaded with a single, clear sentence: 'Get a release by its tag name.' There is no wasted language or redundancy, making it efficient for an AI agent to parse and understand.

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 (3 required parameters) and the presence of an output schema (which handles return values), the description is minimally adequate. However, it lacks behavioral context and usage guidelines, which are important for a GitHub API tool. The completeness is borderline, meeting basic needs but with clear 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%, with clear descriptions for 'owner', 'repo', and 'tag'. The description adds minimal value beyond the schema, only implying that 'tag' refers to a release tag. This meets the baseline of 3, as the schema adequately documents parameters without extra semantic insight 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 clearly states the tool's purpose: 'Get a release by its tag name.' It specifies the verb ('Get') and resource ('release'), and distinguishes it from siblings like 'get_latest_release' and 'list_releases' by focusing on tag-based retrieval. However, it doesn't explicitly differentiate from 'get_tag' or other release-related tools, keeping it at 4 rather than 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 doesn't mention sibling tools like 'get_latest_release' for the most recent release or 'list_releases' for multiple releases, nor does it specify prerequisites or exclusions. This lack of contextual guidance limits its utility for an AI agent.

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 'gets' information, implying a read-only operation, but doesn't disclose critical traits like authentication requirements, rate limits, error handling, or what 'detailed information' entails (e.g., metadata, statistics). For a tool with no annotations, 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 extremely concise with a single sentence that directly states the tool's purpose. It is front-loaded with no wasted words, making it easy to parse. Every part of the sentence 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 (2 required parameters) and the presence of an output schema (which handles return values), the description is reasonably complete for its core purpose. However, it lacks context on usage scenarios, behavioral traits (due to no annotations), and sibling differentiation, which could improve completeness for agent decision-making.

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 'owner' and 'repo' parameters. The description adds no additional meaning beyond the schema, such as format examples (e.g., GitHub usernames) or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but there's no extra value 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 clearly states the tool's purpose with 'Get detailed information about a repository,' which specifies the verb ('Get') and resource ('repository'). It distinguishes from siblings like 'list_repositories' (which lists multiple) and 'create_repository' (which creates new ones). However, it doesn't explicitly mention what 'detailed information' includes, which could be more specific.

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., authentication needs), compare to similar tools like 'get_organization' or 'get_user', or specify use cases (e.g., for repository metadata vs. contents). This leaves 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 describes the recursive behavior option, which is useful context. However, it doesn't mention important behavioral aspects like rate limits, authentication requirements, pagination behavior, error conditions, or what the tree structure output looks like.

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 focused sentences that each earn their place. The first sentence states the core purpose, and the second provides essential usage guidance about the recursive parameter. No wasted words or redundant 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?

Given the tool has an output schema (which handles return values) and 100% schema coverage, the description provides adequate context for a read-only operation. However, for a tool with no annotations, it could benefit from mentioning authentication requirements or rate limits to be fully complete.

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 mentions the recursive parameter's purpose but doesn't provide additional semantic context about parameter interactions or usage nuances.

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 ('Get a repository tree') and resource ('directory listing'), specifying it can be retrieved by SHA or branch name. It distinguishes from sibling tools like get_file_contents (which gets file content) or list_branches (which lists branches without tree structure).

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 about when to use the recursive parameter ('Set recursive=True to get the full nested file tree'), which helps guide usage. However, it doesn't explicitly state when NOT to use this tool versus alternatives like get_file_contents for individual files or list_commits for commit history.

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 discloses that the tool is read-only (implied by 'Get') and specifies it only works for annotated tags, which is useful behavioral context. However, it doesn't mention error handling, authentication needs, rate limits, or response format details, leaving gaps for a tool with no 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 two concise sentences with zero waste. The first sentence states the purpose, and the second provides critical usage guidance. It's front-loaded 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 has an output schema (which handles return values), 100% schema coverage, and no annotations, the description is mostly complete. It clearly defines purpose and usage constraints. However, for a tool with no annotations, it could benefit from mentioning authentication or error scenarios 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?

Schema description coverage is 100%, so the schema already documents all three parameters (owner, repo, tag_sha) with descriptions. The description doesn't add any parameter-specific details beyond what the schema provides, such as format examples or constraints. 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 specific action ('Get an annotated tag object') and resource ('by its SHA'), distinguishing it from sibling tools like 'list_tags' (which lists tags) and 'get_release_by_tag' (which deals with releases). It explicitly differentiates from lightweight tags, showing precise 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 provides explicit usage guidance: 'Only works for annotated tags, not lightweight tags.' This tells the agent when not to use this tool and implies alternatives (e.g., other tools for lightweight tags or general tag listing). It clearly defines the tool's applicability 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 mentions 'public information,' which hints at read-only access and no authentication requirements, but fails to specify rate limits, error conditions (e.g., for non-existent users), or the structure of the returned data. For a tool with zero annotation coverage, this leaves significant behavioral gaps, though it's not misleading.

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 ('Get public information about a GitHub user') with zero wasted words. It's appropriately sized for a simple retrieval tool, making it easy to parse and understand 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 the tool's low complexity (single parameter, read-only operation) and the presence of an output schema (which handles return values), the description is reasonably complete. It covers the basic purpose and scope ('public information'), but could benefit from more behavioral context (e.g., rate limits or error handling) to fully compensate for the lack of annotations, keeping it from a perfect score.

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 'username' parameter clearly documented in the schema. The description adds no additional parameter details beyond what the schema provides, such as format constraints or examples. Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't 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 action ('Get') and resource ('public information about a GitHub user'), making the purpose immediately understandable. It distinguishes this from sibling tools like 'get_authenticated_user' by specifying 'public information' rather than authenticated user data. However, it doesn't explicitly contrast with other user-related tools like 'search_users' or 'list_user_orgs', 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?

The description implies usage context by specifying 'public information,' suggesting this is for retrieving publicly available user data rather than authenticated or private information. However, it provides no explicit guidance on when to use this versus alternatives like 'search_users' (for finding users by criteria) or 'get_authenticated_user' (for the current user's data), leaving some ambiguity in 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?

No annotations are provided, so the description carries full burden. It states it's a listing operation, implying read-only behavior, but doesn't disclose important traits like pagination behavior (implied by parameters but not described), rate limits, authentication requirements, or what the output contains. For a tool with 5 parameters and no 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, clear sentence with zero wasted words. It's appropriately sized for a simple listing tool and front-loads the essential information immediately.

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 (5 parameters, no annotations, but with an output schema), the description is minimally adequate. The output schema existence means return values don't need explanation, but the description lacks context about behavioral aspects (pagination, auth, rate limits) that would help an agent 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 fully documents all 5 parameters. The description adds no parameter-specific information beyond what's in the schema (e.g., it doesn't explain how 'protected' filtering works or clarify pagination behavior). 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 ('List') and resource ('branches in a repository'), making the purpose immediately understandable. However, it doesn't differentiate from similar sibling tools like 'list_tags' or 'list_pull_requests' beyond the resource name, 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. With many sibling tools for listing different repository elements (e.g., 'list_tags', 'list_commits', 'list_pull_requests'), there's no indication of when branches specifically are needed or what distinguishes this listing operation.

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 it's a list operation, implying it's likely read-only and non-destructive, but doesn't mention any behavioral traits like pagination details (implied by parameters but not described), rate limits, authentication needs, or what the output contains. For a tool with 7 parameters and no annotation coverage, 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 a single, efficient sentence that directly states the tool's purpose without any fluff or redundancy. 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 moderate complexity (7 parameters, no annotations, but with an output schema), the description is minimally adequate. The output schema likely covers return values, reducing the need for description details there, but the description lacks behavioral context and usage guidelines, leaving gaps that could hinder effective 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?

Schema description coverage is 100%, meaning all parameters are documented in the input schema with clear descriptions. The description adds minimal value by mentioning the reference types (branch, tag, or SHA), which slightly elaborates on the 'ref' parameter but doesn't provide additional syntax or usage details beyond what the schema already covers. 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 verb ('List') and resource ('check runs') with scope ('for a reference'), making the purpose specific and understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_workflow_runs' or 'list_commit_statuses' that might also relate to repository checks or statuses, 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 'get_check_run' for a single check run or other list tools for different repository entities. It mentions the reference scope but doesn't clarify exclusions or prerequisites, leaving usage context implied at best.

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. It states it's a list operation (implying read-only), but doesn't mention pagination behavior, rate limits, authentication requirements, or what constitutes a 'collaborator' in this context. The description is technically accurate but lacks important operational 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, clear sentence that states exactly what the tool does with zero wasted words. It's appropriately sized for a straightforward list operation and gets directly 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 read-only list operation with comprehensive schema documentation and an output schema, the description is minimally adequate. However, it lacks context about how this tool fits within the broader GitHub API ecosystem or what distinguishes it from similar listing tools. The presence of an output schema reduces the need to describe return values, but more behavioral context would be 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?

The description adds no parameter information beyond what's already in the schema, which has 100% description coverage. The schema fully documents all 5 parameters including their purposes, defaults, and constraints. The description doesn't compensate with any additional context about parameter usage or relationships.

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 ('collaborators of a repository'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'list_org_members' or 'list_user_orgs' that also list people-related entities, so it doesn't reach the highest level of 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. There's no mention of related tools like 'get_authenticated_user' or 'list_org_members' that might serve similar purposes in different contexts, nor any indication of prerequisites or constraints beyond what's in the schema.

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 only states the basic action ('List commits') without mentioning any behavioral traits such as pagination behavior (implied by 'per_page' and 'page' parameters but not described), rate limits, authentication requirements, or whether it's a read-only operation. This leaves significant gaps for an AI agent to understand how the tool behaves beyond its inputs.

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 sentence ('List commits in a repository.'), which is front-loaded and wastes no words. It directly communicates the core purpose without unnecessary elaboration, making it efficient for quick understanding.

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 (8 parameters, no annotations, but with an output schema), the description is minimally adequate. The output schema existence means the description need not explain return values, but it lacks context on behavioral aspects like pagination or error handling. For a list operation with many filtering parameters, more guidance on usage and constraints would improve completeness, but it meets a basic threshold.

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 each parameter well-documented (e.g., 'owner' as 'Repository owner', 'since' as 'ISO 8601 date - only commits after this date'). The description adds no additional meaning beyond what the schema provides, such as explaining relationships between parameters or usage examples. 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 'List commits in a repository' clearly states the verb ('List') and resource ('commits in a repository'), making the purpose immediately understandable. However, it does not differentiate from sibling tools like 'get_commit' (singular) or 'list_pr_commits', which might list commits specific to pull requests, 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. For example, it does not mention when to prefer 'list_commits' over 'get_commit' (for a single commit) or 'list_pr_commits' (for commits in a pull request), nor does it specify any prerequisites or exclusions 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?

No annotations are provided, so the description carries full burden. It states it's a list operation, implying read-only behavior, but doesn't disclose pagination details (implied by parameters), rate limits, authentication needs, or what the output contains. For a tool with no annotations, 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 directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes 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?

Given the tool's moderate complexity (5 parameters, 3 required), 100% schema coverage, and the presence of an output schema, the description is minimally adequate. However, with no annotations, it lacks behavioral details like pagination behavior or error handling, which could be helpful despite the output schema. It meets basic needs but has clear 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 parameters are well-documented in the schema. The description adds minimal value by clarifying that 'ref' includes 'branch, tag, or SHA', but this is already covered in the schema's description for 'ref'. No additional semantics beyond the schema are provided, meeting the baseline of 3.

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') and resource ('commit statuses') with the target ('for a reference'). It distinguishes from siblings like 'list_commits' or 'list_check_runs' by specifying statuses rather than commits or checks. However, it doesn't explicitly differentiate from all possible similar tools, keeping it at 4 instead of 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 doesn't mention sibling tools like 'get_commit' or 'list_check_runs' that might overlap in functionality, nor does it specify prerequisites or exclusions. This leaves the agent without context for 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?

No annotations are provided, so the description carries full burden. It only states what the tool does ('List discussion categories') without disclosing behavioral traits like whether this is a read-only operation, what permissions are required, how results are formatted/paginated, or any rate limits. For a tool with no 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 - a single sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple list operation 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?

Given that an output schema exists (which should document return values), the description doesn't need to explain return values. However, with no annotations and multiple sibling tools that could be confused with this one, the description should provide more context about when to use this specific tool and what behavioral characteristics to expect.

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 ('owner' and 'repo') clearly documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema, so it meets the baseline of 3 for high schema coverage without adding value.

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