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 ('Add') but lacks behavioral details such as required permissions, whether comments are editable/deletable, rate limits, or error handling. The description mentions 'Returns: Comment details or error message', which hints at output but is vague.

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 well-structured with a clear purpose statement followed by 'Args:' and 'Returns:' sections. It's front-loaded and efficient, though the 'Returns' line could be more specific (e.g., describing 'Comment details' further).

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 6 parameters with 0% schema coverage and no annotations, the description partially compensates by explaining parameters and hinting at output. However, as a mutation tool (adding comments), it lacks details on permissions, side effects, and error cases. An output schema exists, so return values needn't be fully described, but behavioral gaps remain.

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 0%, so the description must compensate. It lists all 6 parameters with brief explanations (e.g., 'Comment text (supports markdown)', 'optional if configured'), adding meaningful context beyond the bare schema. However, it doesn't detail formats (e.g., for 'repo_slug') or constraints (e.g., valid 'line' ranges).

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 an inline comment') and target ('on a specific line of code in a Pull Request'), which distinguishes it from sibling tools like 'add_pull_request_comment' (likely general PR comments) and 'add_issue_comment'. However, it doesn't explicitly contrast with these siblings in the description text itself.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'add_pull_request_comment' or 'add_issue_comment'. It mentions the tool's function but offers no context about prerequisites, appropriate scenarios, 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 adds a comment but does not cover critical aspects like required permissions, whether the action is reversible, rate limits, or error handling beyond a vague mention of 'error message'. This leaves significant gaps for an agent to understand the tool's behavior safely.

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 well-structured and front-loaded with the core purpose, followed by clear sections for arguments and returns. Every sentence adds value without redundancy, making it efficient and easy to parse for an agent.

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), the description covers the basic purpose and parameters but lacks behavioral details like permissions or side effects. The presence of an output schema reduces the need to explain return values, but overall completeness is adequate yet with notable gaps for safe 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 description adds meaningful context for parameters beyond the schema, which has 0% coverage. It clarifies that 'content' supports markdown and 'workspace' is optional if configured, providing practical usage details. However, it does not explain 'repo_slug' or 'issue_id' formats, leaving some ambiguity.

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 a comment') and target resource ('to an issue'), which is specific and unambiguous. However, it does not explicitly differentiate from sibling tools like 'add_inline_comment' or 'add_pull_request_comment', which handle comments in different contexts, leaving some potential for confusion.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'add_inline_comment' or 'add_pull_request_comment', nor does it mention prerequisites or exclusions. It lacks context for tool selection, which could lead to misuse in a multi-tool environment.

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 ('Add a comment') but doesn't mention permissions required, rate limits, whether the comment is editable/deletable, or how it interacts with pull request workflows. The mention of markdown support is a useful detail, but overall, critical behavioral context is missing 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 well-structured and front-loaded with the core purpose, followed by parameter explanations and return info. It uses bullet-like formatting for clarity. While efficient, the 'Returns' section could be more specific, but overall, it's concise with minimal waste.

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

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

Given no annotations, 0% schema coverage, and an output schema present, the description does an adequate job. It explains parameters and hints at returns, but as a mutation tool, it lacks details on permissions, side effects, or error handling. The output schema reduces the need to describe return values, but behavioral gaps remain.

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 0%, so the description must compensate. It adds meaning by explaining each parameter's purpose (e.g., 'Repository slug (name)', 'Comment text (supports markdown)') and notes workspace is optional if configured. However, it doesn't clarify formats (e.g., what a 'slug' is) or constraints, leaving gaps despite covering all parameters.

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

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

The description clearly states the action ('Add a comment') and target resource ('to a Pull Request on Bitbucket Cloud'), making the purpose immediately understandable. It distinguishes this tool from siblings like 'add_inline_comment' and 'add_issue_comment' by specifying it's for pull requests. However, it doesn't explicitly contrast with these similar tools, 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 provides no guidance on when to use this tool versus alternatives like 'add_inline_comment' or 'reply_to_comment'. It mentions the workspace parameter is optional 'if configured', which hints at a prerequisite but doesn't explain configuration or usage contexts. There's no explicit when/when-not advice or comparison to sibling tools.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it states the tool adds reviewers without removing existing ones (a useful behavioral detail), it lacks critical information about permissions required, whether the operation is reversible, error conditions, or rate limits. For a mutation tool with zero annotation coverage, this represents significant gaps in behavioral transparency.

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

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

The description is appropriately sized and front-loaded with the core purpose in the first sentence. The parameter explanations are organized clearly under 'Args:' and 'Returns:' sections. While efficient, the 'Returns' section could be slightly more informative about the structure of the 'Updated reviewer list'.

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 operation with 4 parameters), no annotations, and the presence of an output schema (which handles return values), the description is moderately complete. It covers the purpose and parameters adequately but lacks important behavioral context about permissions, side effects, and error handling that would be expected for a mutation tool.

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

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

With 0% schema description coverage, the description compensates well by explaining each parameter's purpose: 'repo_slug: Repository slug (name)', 'pr_id: Pull Request ID', 'reviewer: UUID or account_id of the reviewer to add', and 'workspace: Bitbucket workspace (optional if configured)'. This adds substantial meaning beyond the bare schema, though it could provide more context about format expectations or constraints.

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 ('Add a reviewer to a Pull Request') and resource ('Pull Request'), with explicit differentiation from sibling tools like 'remove_reviewer' by noting 'without removing existing reviewers'. This provides a precise verb+resource combination that distinguishes it from 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 clear context for when to use this tool (to add reviewers without affecting existing ones), but does not explicitly mention when not to use it or name specific alternatives. It implies usage for adding reviewers but lacks explicit exclusions or comparisons to tools like 'approve_pull_request' or 'request_changes_pull_request'.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it states the action ('Approve'), it doesn't explain what approval means in Bitbucket's workflow (e.g., whether it's a final approval, if it affects mergeability, or if it's reversible). It also doesn't mention authentication requirements, rate limits, or error conditions beyond a generic 'error message' reference.

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 well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. However, the 'Args' and 'Returns' sections could be more integrated into the flow rather than separate bullet points, and some phrasing ('optional if configured') is slightly ambiguous, preventing a perfect score.

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 (approval action with 3 parameters), no annotations, and an output schema present, the description is minimally adequate. It covers the basic action and parameters but lacks details on behavioral implications, error handling, and sibling differentiation. The output schema reduces the need to explain return values, but more context is needed for safe and effective use.

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

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

The description includes an 'Args' section that lists parameters with brief explanations, adding value beyond the 0% schema description coverage. However, the explanations are minimal ('Repository slug (name)', 'Pull Request ID to approve') and don't provide format examples, constraints, or how 'workspace' interacts with configuration. This partially compensates for the schema gap but leaves important details unclear.

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 ('Approve') and resource ('a Pull Request on Bitbucket Cloud'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'unapprove_pull_request' or 'decline_pull_request', which would require more specific language about what approval entails versus those alternatives.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'decline_pull_request', 'request_changes_pull_request', or 'unapprove_pull_request'. It also doesn't mention prerequisites such as required permissions or workflow context, leaving the agent without usage context beyond the basic action.

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 must fully disclose behavioral traits. It states the tool creates a branch and returns details or an error, but lacks critical information such as required permissions, whether it's idempotent, potential side effects (e.g., branch naming conflicts), or rate limits. 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 well-structured with clear sections (purpose, args, returns) and uses bullet points for readability. It's front-loaded with the main purpose, and each sentence adds value without redundancy. A slight improvement could be merging the args list into a more concise narrative, but overall it's efficient.

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

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

Given the tool's complexity (a mutation with 4 parameters), no annotations, and an output schema present (which handles return values), the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral details like error conditions or usage context. This is the minimum viable for such a tool, with clear room for enhancement.

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 0%, so the description must compensate. It lists all four parameters with brief explanations (e.g., 'target' as 'Commit hash, branch name, or tag to branch from'), which adds meaningful context beyond the schema's type definitions. However, it doesn't cover constraints like format requirements or examples, leaving some 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 ('Create a new branch') and resource ('in a repository'), which is specific and unambiguous. However, it does not explicitly differentiate from sibling tools like 'create_tag' or 'fork_repository', which also create things in repositories, so it misses the top 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. For example, it doesn't mention when to use 'create_branch' compared to 'create_pull_request' or 'fork_repository', nor does it specify prerequisites like repository access or authentication needs. This leaves the agent with minimal 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?

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation (implying mutation/write), but doesn't mention required permissions, authentication needs, rate limits, error handling, or whether the operation is idempotent. The description adds minimal behavioral context 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 well-structured with clear sections (Args, Returns) and uses bullet-point-like formatting. The opening sentence directly states the purpose, followed by organized parameter documentation. While slightly verbose due to listing all parameters, every sentence adds value and there's no 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's complexity (8 parameters, mutation operation) and lack of annotations, the description provides good parameter documentation but lacks behavioral context. The presence of an output schema means the description doesn't need to detail return values, but it should address permissions, error cases, and usage context more thoroughly for a mutation tool.

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

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

With 0% schema description coverage, the description provides significant value by documenting all 8 parameters with clear explanations. It specifies which parameters are required versus optional, provides the exact enum values for 'state', and clarifies the purpose of each parameter (e.g., 'key' as 'Unique key for this build status'). This compensates well for the schema's lack of 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 a build status') and target resource ('for a commit'), using precise terminology. It distinguishes this tool from sibling tools like 'create_issue' or 'create_pull_request' by focusing specifically on build statuses for commits, not other Bitbucket entities.

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. While sibling tools include 'list_commit_statuses' which might retrieve existing statuses, there's no explicit comparison or context about when creation versus listing is appropriate. No prerequisites, exclusions, or workflow context are mentioned.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a creation operation but doesn't mention required permissions, whether it's idempotent, rate limits, or error conditions beyond 'error message'. For a write 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 well-structured with clear sections (purpose, args, returns) and uses bullet-like formatting. While efficient, the 'Args:' and 'Returns:' headers could be more integrated with the main text, and some phrasing ('optional if configured') could be slightly tightened.

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 (7 parameters, write operation) and no annotations, the description does well by documenting all parameters and noting the output schema exists. However, it lacks behavioral context (permissions, side effects) that would be crucial for safe agent use, preventing 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?

With 0% schema description coverage, the description fully compensates by providing comprehensive parameter documentation: it explains all 7 parameters, including optional status, defaults, enums for kind/priority, and format guidance (e.g., 'markdown', 'Account ID'). This adds substantial value beyond the bare schema.

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

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

The description clearly states the specific action ('Create a new issue') and resource ('in a repository's issue tracker'), distinguishing it from sibling tools like 'update_issue' or 'list_issues'. It precisely communicates the tool's function without ambiguity.

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 through parameter documentation (e.g., 'optional if configured' for workspace), but lacks explicit guidance on when to use this tool versus alternatives like 'update_issue' or prerequisites. It provides basic parameter context but no strategic usage advice.

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 this is a creation operation but doesn't mention permission requirements, whether the variable is immediately available for pipelines, if there are rate limits, or what happens on duplicate keys. The return statement mentions 'Created variable details or error message' but lacks specifics about format or error conditions.

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 well-structured with a clear purpose statement followed by organized Args and Returns sections. Every sentence adds value, though the 'Returns' section could be slightly more specific about what 'details' includes. No redundant information is present.

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

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

For a creation tool with no annotations, 0% schema description coverage, but an output schema present, the description does reasonably well. It covers parameter semantics thoroughly and mentions return values generally. However, it lacks important behavioral context about permissions, idempotency, and error handling that would be needed for safe 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?

The description provides clear semantic explanations for all 5 parameters beyond the 0% schema description coverage. It explains what 'repo_slug', 'key', 'value', and 'secured' mean, notes defaults for 'secured' and 'workspace', and clarifies that 'workspace' is optional if configured. This effectively compensates for the lack of 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 action ('Create a pipeline variable') and resource ('for a repository'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_pipeline_variables' or explain how this creation differs from other variable-related operations that might exist.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing repository access), compare with sibling tools like 'list_pipeline_variables', or specify scenarios where creating a pipeline variable is appropriate versus other configuration methods.

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 this is a creation operation but doesn't mention required permissions, whether the project key must be globally unique, what happens on duplicate keys, rate limits, or authentication requirements. The 'Returns' section mentions error messages but doesn't describe success/failure patterns.

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 efficiently structured with a clear purpose statement followed by Args and Returns sections. Every sentence adds value, though the 'Returns' line could be more specific about what 'Created project details' includes. The formatting helps readability without unnecessary verbosity.

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

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

Given the complexity of a creation tool with 5 parameters, no annotations, but with an output schema (which reduces the need to describe return values), the description is moderately complete. It covers parameter semantics well but lacks behavioral context like permissions, error handling details, and sibling tool differentiation that would make it 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?

With 0% schema description coverage, the description compensates well by explaining all 5 parameters: it clarifies that 'key' must be uppercase letters and numbers, 'description' is optional, 'is_private' defaults to True, and 'workspace' is optional if configured. This adds significant value beyond the bare schema, though it doesn't specify length limits or validation rules for 'name' and 'key'.

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 project in a workspace'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'create_repository' or 'create_snippet' beyond the resource type, 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 'create_repository' or 'list_projects'. It mentions that 'workspace' is optional if configured, which is a minor usage hint, but lacks explicit when/when-not instructions or sibling tool 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?

No annotations are provided, so the description carries the full burden. It mentions that the tool returns 'PR details including URL and ID, or error message', which adds some behavioral context about outputs. However, it lacks critical details like authentication requirements, rate limits, side effects (e.g., notifications to reviewers), or error conditions beyond the generic mention.

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 well-structured with clear sections for 'Args' and 'Returns', making it easy to scan. It is appropriately sized for an 8-parameter tool, with no redundant sentences. However, the 'Args' section is somewhat dense and could benefit from bullet points for better readability.

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 (8 parameters, no annotations, but with an output schema), the description is mostly complete. It covers all parameters and hints at return values, though it lacks behavioral details like authentication or error handling. The presence of an output schema reduces the need to fully describe returns, but more context on usage scenarios 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?

With 0% schema description coverage, the description compensates by explaining all 8 parameters in the 'Args' section, including semantics like 'Repository slug (name)', 'PR title', and optional/default values (e.g., 'default: main', 'optional'). This adds significant meaning beyond the bare schema, though it could be more detailed on formats (e.g., UUID format for reviewers).

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 a Pull Request') and the target resource ('on Bitbucket Cloud'), distinguishing it from sibling tools like 'update_pull_request' or 'get_pull_request'. It uses precise terminology that matches the tool's name without being tautological.

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

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

The description implies usage through the tool's name and context, but does not explicitly state when to use this tool versus alternatives like 'update_pull_request' or 'merge_pull_request'. It provides no guidance on prerequisites, such as requiring an existing repository or branch.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates this is a creation operation (implying mutation) and mentions the return format ('Created repository details or error message'), but doesn't address important behavioral aspects like authentication requirements, rate limits, error conditions, or what happens on duplicate repository names. It provides basic behavioral context but misses key operational details.

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 well-structured with clear sections (purpose, Args, Returns) and uses bullet-like formatting for parameters. While efficient, the parameter explanations could be slightly more concise, and the 'Returns' section could be integrated more smoothly. Overall, it's front-loaded and organized with minimal waste.

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 (7 parameters, creation operation), no annotations, but with an output schema present, the description provides good coverage. It explains all parameters thoroughly and mentions the return format. The main gap is lack of behavioral context like authentication needs or error handling, but the parameter documentation is excellent and the output schema handles return values.

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 0% schema description coverage and 7 parameters, the description provides comprehensive parameter documentation in the 'Args' section, explaining each parameter's purpose, optionality, defaults, and valid values (e.g., fork_policy options). This fully compensates for the schema's lack of descriptions and adds significant value beyond the bare schema.

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

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

The description clearly states the specific action ('Create a new repository') and resource ('in a Bitbucket workspace'), distinguishing it from sibling tools like 'fork_repository' or 'update_repository'. It provides a complete verb+resource+scope statement that leaves no ambiguity about the tool's 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 implies usage context through the mention of Bitbucket workspace and optional parameters, but doesn't explicitly state when to use this tool versus alternatives like 'fork_repository' or 'create_project'. It provides basic context but lacks explicit guidance on tool selection scenarios.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool creates a snippet and mentions a return value, but fails to describe critical behaviors like required permissions, error handling, side effects, or rate limits. 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 structured with clear sections (Args, Returns) but includes redundant phrasing ('Create a new snippet' followed by parameter details). The 'Args' and 'Returns' labels are helpful, but the content could be more front-loaded and concise, with some sentences not adding significant value beyond listing parameters.

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

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

Given 5 parameters with 0% schema coverage and no annotations, the description partially compensates by listing parameters and noting an output schema exists. However, for a mutation tool, it lacks details on permissions, errors, or behavioral context, making it incomplete despite the output schema covering return values.

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 0%, so the description must compensate. It lists all 5 parameters with brief explanations (e.g., 'Snippet title', 'Filename for the snippet content'), adding basic semantics beyond the bare schema. However, it doesn't elaborate on constraints, formats, or interactions between parameters, leaving gaps in 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 a new snippet') and identifies the resource ('snippet'), which is specific and unambiguous. However, it doesn't differentiate this tool from sibling tools like 'create_repository' or 'create_issue' beyond the resource type, missing 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. The description lacks context about prerequisites (e.g., authentication), use cases, or comparisons to sibling tools like 'list_snippets' or 'delete_snippet', leaving the agent without usage direction.

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

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

No annotations are provided, so the description carries full burden. It states this is a creation operation but doesn't disclose behavioral traits like required permissions, whether it's idempotent, what happens if a tag with the same name exists, rate limits, or authentication needs. The mention of 'error message' in returns hints at potential failures but lacks specifics.

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 well-structured with clear sections (Args, Returns) and uses bullet points for readability. It's appropriately sized for a 4-parameter tool, with no redundant information. However, the 'Returns' section could be more concise by leveraging the output schema.

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

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

Given the complexity (creation tool with 4 parameters), no annotations, and an output schema present, the description is moderately complete. It covers basic purpose and parameters but lacks behavioral context (permissions, idempotency) and usage guidelines. The output schema reduces the need to detail return values, but the description still misses key operational insights.

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 0%, so the description must compensate. It lists all 4 parameters with brief explanations (e.g., 'Repository slug (name)', 'Commit hash to tag'), adding meaning beyond the bare schema. However, it doesn't provide format details (e.g., slug conventions, hash length), validation rules, or examples, leaving gaps in 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 a new tag') and resource ('in a repository'), making the purpose immediately understandable. It distinguishes from sibling tools like 'delete_tag' and 'list_tags' by specifying creation rather than deletion or listing. However, it doesn't explicitly differentiate from other creation tools like 'create_branch' or 'create_issue' 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. There's no mention of prerequisites (e.g., needing repository access), when not to use it (e.g., if a tag already exists), or comparisons to similar tools like 'create_branch' or 'create_issue'. The optional workspace parameter is noted but without context on when it's needed.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that the tool 'Creates a webhook' and returns 'Created webhook details or error message', but lacks details on permissions required, rate limits, whether the webhook is immediately active, or how errors are handled. 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 well-structured with a clear purpose statement followed by 'Args' and 'Returns' sections. It is appropriately sized with no redundant sentences, though the 'Args' section could be slightly more concise by integrating some details into the main description.

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

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

Given that there is an output schema (which handles return values), the description does not need to explain returns in detail. However, as a mutation tool with no annotations and 6 parameters, the description should provide more behavioral context (e.g., authentication needs, error conditions). The parameter explanations are good, but overall completeness is moderate due to missing operational details.

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 0% schema description coverage, the description compensates by explaining all 6 parameters in the 'Args' section, adding meaning beyond the bare schema. It clarifies optional vs. required parameters, provides examples for 'events', and notes defaults for 'active' and 'workspace'. However, it doesn't specify format constraints (e.g., URL validation) or event enum values.

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 webhook') and the target resource ('for a repository'), making the purpose specific and unambiguous. It distinguishes itself from sibling tools like 'delete_webhook' and 'list_webhooks' by focusing on creation rather than deletion or listing.

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

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

The description implies usage when needing to set up a webhook for repository events, but does not explicitly state when to use this tool versus alternatives like 'list_webhooks' for checking existing webhooks or 'delete_webhook' for removal. No exclusions or prerequisites are mentioned, leaving usage context partially inferred.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it states the action is to 'decline/close' (implying a destructive mutation), it doesn't mention permission requirements, whether the action is reversible, rate limits, or what specific confirmation message format to expect. For a destructive operation with zero annotation coverage, this is insufficient.

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

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

The description is efficiently structured with a clear purpose statement followed by well-organized parameter explanations and return information. Every sentence adds value, though the 'Args:' and 'Returns:' formatting could be slightly more concise.

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 but with an output schema (implied by 'Returns: Confirmation or error message'), the description covers the basic purpose and parameters adequately. However, for a tool that permanently closes pull requests, more behavioral context about permissions, irreversibility, and error conditions would be beneficial.

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 0% schema description coverage, the description provides meaningful semantic context for all 4 parameters: 'repo_slug' is explained as 'Repository slug (name)', 'pr_id' as 'Pull Request ID to decline', 'reason' as 'Optional reason for declining (will be added as a comment)', and 'workspace' as 'Bitbucket workspace (optional if configured)'. This compensates well for the schema's lack of 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 ('Decline/close a Pull Request'), specifies the resource ('on Bitbucket Cloud'), and distinguishes it from alternatives by explicitly stating 'without merging'. This differentiates it from sibling tools like 'merge_pull_request' and 'update_pull_request'.

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 by stating this tool declines/close pull requests 'without merging', which implicitly suggests when to use it versus merging alternatives. However, it doesn't explicitly mention when NOT to use it or name specific alternative tools beyond the implied contrast with merging.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool deletes a branch but lacks critical details such as permissions required, whether the deletion is permanent or reversible, or any side effects (e.g., impact on open pull requests). This is inadequate 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 well-structured with clear sections for purpose, arguments, and returns, making it easy to scan. It is concise with no unnecessary information, though the 'Args' and 'Returns' labels could be more integrated into the flow.

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 destructive nature, lack of annotations, and 0% schema coverage, the description is incomplete—it misses behavioral details like safety warnings or error handling. However, the presence of an output schema reduces the need to explain return values, and the parameter descriptions partially compensate for schema 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?

The description includes an 'Args' section that names and briefly describes the three parameters, adding value beyond the schema (which has 0% description coverage). However, it does not provide detailed semantics like format examples or constraints, leaving gaps in 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 ('Delete') and resource ('a branch from a repository'), making the purpose immediately understandable. However, it does not explicitly differentiate from sibling tools like 'delete_repository' or 'delete_tag', 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., other deletion tools like 'delete_repository' or 'delete_tag'), nor does it mention prerequisites or conditions for use. The description only states what it does without context.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('Delete') which implies a destructive mutation, but doesn't clarify if this is reversible, what permissions are required, or any rate limits. The 'Returns' section mentions a confirmation or error message, but doesn't describe the format or common error scenarios. 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 well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. Each section serves a purpose, though the 'Returns' line could be more specific. There's no redundant information, making it efficient while covering the basics.

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 tool with no annotations, 4 parameters (3 required), 0% schema description coverage, but with an output schema, the description does an adequate job. It explains what the tool does and documents parameters, but lacks important behavioral context (permissions, irreversibility) and doesn't leverage the output schema to describe return values more specifically. The presence of an output schema reduces the burden slightly, but not enough for a higher 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 description includes an 'Args' section that lists all 4 parameters with brief explanations, adding meaning beyond the 0% schema description coverage. It clarifies that 'workspace' is optional if configured, which is helpful context. However, it doesn't provide format details (e.g., what a 'repository slug' looks like) or constraints beyond what's implied by the schema types.

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 ('a comment from a Pull Request'), which is specific and unambiguous. It distinguishes this tool from sibling tools like 'delete_branch' or 'delete_repository' by specifying the resource type. However, it doesn't explicitly differentiate from other comment-related tools like 'reply_to_comment' in terms of purpose.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing appropriate permissions), when deletion is appropriate (e.g., for cleanup vs. moderation), or what happens after deletion (e.g., irreversibility). There's no comparison to sibling tools like 'delete_repository' or context about Bitbucket workflows.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates the critical behavioral trait: 'This action is irreversible,' which is essential for a destructive operation. However, it doesn't mention authentication requirements, rate limits, or what happens to associated data (branches, issues, etc.).

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 well-structured and appropriately sized, with a clear purpose statement upfront, followed by parameter and return value sections. Every sentence adds value, though the 'Returns' section could be slightly more informative given the output schema exists.

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 tool with no annotations, 2 parameters (0% schema coverage), and an output schema, the description does a good job covering essentials: purpose, irreversibility, and parameter meanings. However, it lacks details on error conditions, permissions, or side effects, which would enhance completeness for such a high-stakes 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 0%, so the description must compensate. It provides basic semantic context for both parameters ('repo_slug: Repository slug (name)' and 'workspace: Bitbucket workspace (optional if configured)'), explaining what they represent. However, it doesn't clarify format details (e.g., slug syntax) or the 'optional if configured' condition, leaving some gaps.

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

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

The description clearly states the specific action ('Delete') and resource ('a repository'), distinguishing it from sibling tools like 'create_repository' or 'fork_repository'. It provides a precise verb+resource combination that leaves no ambiguity about the tool's 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 implies usage context through the warning 'This action is irreversible,' suggesting it should be used cautiously. However, it doesn't explicitly state when to use this tool versus alternatives (like 'delete_branch' or 'delete_snippet') or provide clear prerequisites or exclusions.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that it returns a 'Confirmation or error message', which hints at the outcome but doesn't specify whether deletion is permanent, reversible, requires specific permissions, or has side effects (e.g., affecting linked content). For a destructive operation, this is insufficient detail.

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 front-loaded with the core action ('Delete a snippet'), followed by structured sections for Args and Returns. It's efficient with minimal waste, though the Args section could be integrated more smoothly. Every sentence serves a purpose, making it clear and easy to scan.

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 (destructive operation with 2 parameters, 0% schema coverage, no annotations, but with an output schema), the description is minimally adequate. It covers the basic action and parameters but lacks critical details like permissions, irreversibility, and error conditions. The output schema helps, but the description should do more to compensate for missing annotations.

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 lists the parameters ('snippet_id' and 'workspace') and notes that workspace is optional if configured, adding context beyond the schema's 0% coverage. However, it doesn't explain what a 'snippet_id' is (e.g., format, where to find it) or how the optional workspace interacts with configuration, leaving gaps in 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 states the action ('Delete') and resource ('a snippet'), which is clear but basic. It doesn't differentiate from sibling tools like 'delete_branch', 'delete_repository', or 'delete_tag', which all follow the same pattern. The purpose is understandable but lacks specificity about what makes deleting a snippet unique in this context.

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

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing snippet permissions), when deletion is appropriate, or how it relates to other tools like 'get_snippet' or 'list_snippets'. The description only states what it does, not when to use it.

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

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

No annotations are provided, so the description carries the full burden. It states the action is a deletion but doesn't disclose critical behavioral traits such as whether deletion is permanent/reversible, permission requirements, side effects, or rate limits. This is inadequate 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 appropriately sized and front-loaded with the core purpose, followed by structured parameter and return sections. Every sentence earns its place, though the 'Returns' line could be more specific.

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 destructive nature, lack of annotations, and an output schema (implied by 'Has output schema: true'), the description is moderately complete. It covers parameters and basic purpose but misses behavioral context and detailed usage guidelines, which are crucial for a deletion tool.

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

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

With 0% schema description coverage, the description compensates by explaining all three parameters: 'repo_slug' (repository slug/name), 'name' (tag name to delete), and 'workspace' (optional Bitbucket workspace). It adds meaning beyond the bare schema, though it could detail format constraints.

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

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

The description clearly states the specific action ('Delete a tag') and resource ('from a repository'), distinguishing it from sibling tools like 'create_tag' or 'list_tags'. It uses precise terminology that aligns with the tool's name without being tautological.

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

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

The description provides no guidance on when to use this tool versus alternatives like 'delete_branch' or 'delete_repository', nor does it mention prerequisites or context for deletion. It lacks explicit when/when-not instructions or named alternatives.

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 if this is permanent, requires specific permissions, or has side effects. The mention of 'Confirmation or error message' in returns adds minimal context about response format.

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 efficiently structured with a clear purpose statement followed by organized Args and Returns sections. Every sentence serves a purpose, though the returns statement could be slightly more specific about what 'Confirmation' entails.

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

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

Given this is a destructive mutation tool with no annotations and an output schema exists, the description is moderately complete. It covers parameters well and mentions return types, but lacks important context about permissions, irreversibility, and relationship to sibling tools like 'list_webhooks' that would typically precede this 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?

With 0% schema description coverage, the description compensates well by explaining all three parameters: 'repo_slug' as repository name, 'webhook_uid' as UUID format with brace details, and 'workspace' as optional Bitbucket workspace. This adds crucial semantic meaning beyond the bare schema types.

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 explicitly differentiate from sibling tools like 'delete_repository' or 'delete_tag' beyond the resource type, 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_webhooks' for checking existing webhooks or 'create_webhook' for creating them. It also doesn't mention prerequisites such as needing the webhook UUID from a list operation first.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action ('Fork a repository') but doesn't describe what forking entails (creates a copy, maintains link to original), permission requirements, rate limits, or what happens if the repository already exists. The mention of 'Returns: Forked repository details or error message' adds minimal behavioral context.

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

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

The description is appropriately sized and front-loaded with the core purpose. The Args/Returns structure is clear, though slightly redundant with schema. Every sentence earns its place, but the 'Returns' line could be more informative given the output schema exists.

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 3 parameters with 0% schema coverage and no annotations, the description provides basic parameter semantics but lacks behavioral context for a mutation operation. The existence of an output schema means return values don't need explanation, but the description should do more to explain the fork operation's implications, permissions, and error conditions.

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 0%, so the description must compensate. It provides basic semantic meaning for all three parameters: 'repo_slug' as the repository to fork, 'new_name' as optional name for the fork, and 'workspace' as optional Bitbucket workspace. However, it doesn't explain format requirements (e.g., slug conventions), default behaviors beyond 'new_name', or when workspace is required versus optional.

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

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

The description clearly states the action ('Fork a repository') with a specific verb and resource. It distinguishes this from sibling tools like 'create_repository' or 'list_repository_forks' by focusing on the fork operation. However, it doesn't explicitly contrast with these siblings in the description text itself.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (like authentication or permissions), when forking is appropriate versus creating a new repository, or how it differs from 'list_repository_forks'. The agent must infer usage context from the tool name alone.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves configuration details, implying a read-only operation, but does not specify error conditions (e.g., if the repository doesn't exist), authentication requirements, rate limits, or whether the data is cached. 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 well-structured and front-loaded with the core purpose, followed by clear sections for arguments and returns. Every sentence adds value, with no redundant information. It could be slightly more concise by integrating the optional note into the parameter list, but overall it is 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 low complexity (simple retrieval), 2 parameters with semantic clarification in the description, and the presence of an output schema (which handles return details), the description is largely complete. It covers the what, parameters, and returns adequately, though it lacks behavioral context like error handling or prerequisites, which holds it back 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 description adds meaningful context for both parameters: 'repo_slug' is clarified as the repository name, and 'workspace' is noted as optional if configured, which helps understand when it can be omitted. With 0% schema description coverage, this compensates well, though it could detail format constraints (e.g., slug format) or default behaviors more explicitly.

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 ('branching model configuration for a repository'), distinguishing it from sibling tools that focus on operations like creating branches, pull requests, or repositories. It precisely identifies what is being retrieved without ambiguity.

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

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

The description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, such as whether the repository must exist or have a configured branching model, nor does it differentiate from other configuration-related tools like 'get_config_status' or 'get_repository'. Usage context is implied but not explicitly stated.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get details'), which implies safety, but doesn't mention authentication requirements, rate limits, error conditions, or what happens if the commit doesn't exist. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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

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

The description is well-structured with a clear purpose statement followed by Args and Returns sections. It's appropriately sized with no redundant information. The only minor improvement would be integrating the parameter explanations more seamlessly rather than as a separate list.

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 parameters, no annotations, but has output schema), the description is reasonably complete. It explains all parameters and return values ('Commit details including message, author, date, and parents'). The output schema existence means it doesn't need to detail return structure, but it could better address behavioral aspects like error handling.

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 0%, so the description must compensate. It clearly explains all three parameters: 'repo_slug' as 'Repository slug (name)', 'commit_hash' as 'The commit hash', and 'workspace' as 'Bitbucket workspace (optional if configured)'. This adds meaningful context beyond the bare schema types, though it could elaborate on format expectations (e.g., hash length).

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 details') and resource ('a specific commit'), distinguishing it from sibling tools like 'list_commits' (which lists multiple commits) and 'get_commit_diff' (which focuses on changes). It precisely communicates the tool's function without redundancy.

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_commits' or 'get_pull_request_commits'. It mentions the workspace parameter is optional if configured, but offers no context about prerequisites, dependencies, or typical use cases for commit details retrieval.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool returns 'diff content as text', which is useful, but lacks critical details: whether this is a read-only operation, any rate limits, authentication requirements, error conditions, or format specifics (e.g., unified diff). 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 efficiently structured with a clear purpose statement followed by well-organized Args and Returns sections. Every sentence earns its place by providing essential information without redundancy. The formatting with bullet-like sections enhances readability while maintaining brevity.

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

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

Given the tool's moderate complexity (3 parameters, no annotations, but has output schema), the description is reasonably complete. The output schema exists, so the description doesn't need to detail return values beyond stating 'diff content as text'. It covers parameter semantics well despite 0% schema coverage. However, the lack of behavioral context (especially with no annotations) prevents 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?

Schema description coverage is 0%, so the description must compensate. It provides clear semantic explanations for all three parameters: repo_slug as 'Repository slug (name)', spec as 'Commit hash or range' with examples, and workspace as 'Bitbucket workspace (optional if configured)'. This adds substantial value beyond the bare schema, though it doesn't cover all possible edge cases (e.g., format of repo_slug).

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 the diff') and resource ('for a commit or commit range'), distinguishing it from siblings like get_commit (which retrieves commit metadata) or get_pull_request_diff (which focuses on pull requests). The verb+resource combination is precise and 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 implies usage for retrieving diff content from commits, but provides no explicit guidance on when to choose this over alternatives like get_commit_diffstat (for statistics) or get_pull_request_diff (for pull request diffs). It mentions the workspace parameter is optional if configured, which offers some context but doesn't address tool selection.

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

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

With no annotations provided, the description carries full burden. It states the tool is a read operation ('Get') and describes the return format, but doesn't disclose behavioral traits like authentication requirements, rate limits, error conditions, or whether it's a safe operation. The description adds basic context but lacks important operational details.

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?

Perfectly structured with a clear purpose statement followed by organized sections for Args and Returns. Every sentence earns its place - the first sentence establishes purpose, parameter explanations are essential, and the return statement is necessary. No wasted words.

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

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

For a read-only tool with 3 parameters and an output schema, the description is quite complete. It covers purpose, all parameters with semantics, and return format. The main gap is lack of behavioral context (auth, errors, limits) which would be helpful despite the output schema. Given the tool's relative simplicity, it's mostly adequate.

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 0% schema description coverage, the description fully compensates by explaining all 3 parameters: 'repo_slug' as repository name, 'spec' as commit hash or range with examples, and 'workspace' as optional Bitbucket workspace. This adds crucial semantic meaning beyond the bare schema types.

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 the diffstat'), resource ('for a commit or commit range'), and output format ('summary of changes'). It distinguishes from sibling tools like 'get_commit_diff' (full diff) and 'get_pull_request_diffstat' (PR-specific) by focusing on commit-level diffstat.

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 through the parameter explanations (e.g., 'optional if configured' for workspace), but doesn't explicitly state when to use this tool versus alternatives like 'get_commit_diff' or 'get_pull_request_diffstat'. No explicit exclusions or prerequisites are provided.

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

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

No annotations are provided, so the description must fully disclose behavioral traits. It states the tool checks configuration status and returns workspace info, but lacks details on what 'configured' means (e.g., authentication, permissions), whether it's a read-only operation (implied but not explicit), error handling, or performance aspects. For a tool with zero annotation coverage, this is insufficient 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 concise and front-loaded, with the core purpose in the first sentence and return details in the second. Both sentences are relevant, though the second could be integrated more smoothly. There's no wasted verbiage, making it efficient for agent comprehension.

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 (0 parameters, output schema provided), the description is somewhat complete but has gaps. It covers the basic action and return value, but lacks usage context and behavioral details. With an output schema, it doesn't need to explain return values, but should address when and why to use this tool, especially relative to siblings like 'setup_bitbucket'.

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

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details, which is appropriate. A baseline of 4 is applied since the schema fully handles parameters, and the description doesn't need to compensate.

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: 'Check if Bitbucket is configured and return current status.' It uses specific verbs ('check', 'return') and identifies the resource (Bitbucket configuration). However, it doesn't explicitly differentiate from sibling tools like 'get_workspace_details' or 'setup_bitbucket', which might have overlapping concerns with configuration status.

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., whether Bitbucket must be set up first), compare to siblings like 'setup_bitbucket' (for configuration) or 'get_workspace_details' (for workspace info), or specify use cases (e.g., diagnostic checks). 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 the full burden. It discloses that the tool retrieves profile information, indicating a read-only operation, but lacks details on authentication requirements, rate limits, or error behaviors. The description adds basic context but misses deeper behavioral traits.

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 front-loaded with the core purpose in the first sentence and uses a 'Returns:' section efficiently to detail output without redundancy. Both sentences earn their place by providing essential information in a compact format.

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

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

Given the tool's simplicity (0 parameters, no annotations, but has an output schema), the description is mostly complete. It explains what the tool does and what it returns, but could benefit from more behavioral context like authentication details. The output schema likely covers return values, reducing the need for extensive description.

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

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter semantics beyond the schema, but since there are no parameters, this is acceptable. Baseline is 4 as per rules for 0 parameters.

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

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

The description clearly states the specific action ('Get') and resource ('currently authenticated user's profile information'), distinguishing it from sibling tools like 'get_user_profile' or 'get_user_permissions' by focusing on the current session's user rather than a specified user. It provides explicit differentiation in purpose.

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

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

The description implies usage context by specifying 'currently authenticated user,' suggesting it should be used for retrieving the profile of the user associated with the current session. However, it does not explicitly state when to use this tool versus alternatives like 'get_user_profile' or provide exclusions, leaving some ambiguity.

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

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

With no annotations provided, the description carries the full burden. It discloses the tool's read-only nature implicitly through 'Get', but lacks details on permissions required, rate limits, error conditions, or pagination. The return format is described, adding some behavioral context, but critical operational traits 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 well-structured with a clear purpose statement followed by Args and Returns sections. It's appropriately sized with no redundant information, though the 'Args' and 'Returns' labels could be integrated more seamlessly into the flow.

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

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

Given the tool's moderate complexity (2 parameters, read-only operation), the description is reasonably complete. It covers purpose, parameters, and return values. With an output schema present, detailed return explanations are unnecessary. However, it lacks context on authentication needs or error handling, leaving minor gaps.

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

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

Schema description coverage is 0%, so the description must compensate. It explains the meaning of 'repo_slug' as 'Repository slug (name)' and 'workspace' as 'Bitbucket workspace (optional if configured)', adding semantic clarity beyond the bare schema. However, it doesn't detail format constraints (e.g., slug patterns) or default behaviors when workspace is omitted.

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') and resource ('default reviewers configured for a repository'), distinguishing it from sibling tools like 'add_reviewer' or 'remove_reviewer'. It precisely defines what the tool retrieves without ambiguity.

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 for retrieving default reviewers, but provides no explicit guidance on when to use this tool versus alternatives (e.g., 'get_user_permissions' for reviewer permissions) or prerequisites. It mentions the workspace parameter is optional 'if configured', which offers some contextual hint but not comprehensive alternatives.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action is a read operation ('Get'), which implies non-destructive behavior, but doesn't mention authentication requirements, rate limits, error conditions, or response formats beyond 'File contents as text'. This leaves gaps in understanding the tool's full 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 well-structured and front-loaded with the core purpose, followed by organized parameter and return value sections. Every sentence adds value without redundancy, making it efficient and easy to parse for both humans and AI agents.

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, 2 required), no annotations, and an output schema present (implied by 'Returns'), the description is mostly complete. It covers purpose, parameters, and return values adequately, though it could benefit from more behavioral context (e.g., error handling) to fully compensate for the lack of annotations.

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 provides detailed parameter semantics in the 'Args' section, explaining each parameter's purpose (e.g., 'ref' as 'Branch name, tag, or commit hash'), which compensates for the 0% schema description coverage. It clarifies optionality and defaults, adding significant value beyond the bare schema, though it doesn't cover edge cases or format examples.

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 the contents of a file') and resource ('from a repository at a specific branch/commit'), distinguishing it from sibling tools like 'get_commit' or 'search_code' that operate on different resources. It precisely defines the tool's scope without being vague or tautological.

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

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

The description implies usage when file contents are needed from a repository, but lacks explicit guidance on when to use this tool versus alternatives like 'get_commit' (for metadata) or 'search_code' (for broader searches). No exclusions or prerequisites are mentioned, leaving usage context partially inferred rather than clearly defined.

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

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states it 'Get details' which implies a read-only operation, but doesn't clarify if it requires specific permissions, rate limits, error conditions, or what happens if the issue doesn't exist. The 'Returns' section mentions output fields but lacks depth on format or pagination.

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

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

The description is appropriately sized and front-loaded with the main purpose in the first sentence. The 'Args' and 'Returns' sections are structured for clarity, though the 'Returns' section could be more concise by listing fewer examples or integrating with the output schema. No wasted sentences, but minor verbosity in the returns list.

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 reduces the need to explain return values in the description) and no annotations, the description is moderately complete. It covers the basic purpose and parameters but lacks behavioral details like error handling or usage context. For a simple read operation, this is adequate but has clear gaps in guidelines and 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 0%, so the schema provides no parameter descriptions. The description adds value by explaining 'repo_slug' as 'Repository slug (name)', 'issue_id' as 'Issue ID', and 'workspace' as 'Bitbucket workspace (optional if configured)', which clarifies their roles. However, it doesn't fully compensate for the coverage gap by detailing formats (e.g., slug conventions) or when 'workspace' is required.

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 as 'Get details of a specific issue' with a specific verb ('Get') and resource ('issue'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'list_issues' or 'get_issue_comments', which would require mentioning it retrieves a single issue by ID rather than listing multiple issues or getting 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. It doesn't mention sibling tools like 'list_issues' for browsing issues or 'update_issue' for modifying issues, nor does it specify prerequisites such as authentication or repository access. The optional 'workspace' parameter is noted but without context on when it's needed.

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, it doesn't specify authentication requirements, rate limits, error conditions, or what happens if the pipeline doesn't exist. The description adds minimal behavioral context beyond the basic 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 well-structured and appropriately sized. It front-loads the purpose, then lists parameters with brief explanations, and ends with return details. Each sentence adds value, though the parameter explanations could be slightly more concise.

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 parameters, 2 required) and the presence of an output schema (which handles return value documentation), the description is reasonably complete. It covers the purpose, parameters, and return scope, though it lacks behavioral details and usage guidelines that would be helpful 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 0%, but the description provides semantic explanations for all three parameters: 'repo_slug: Repository slug (name)', 'pipeline_uuid: Pipeline UUID (with or without braces)', and 'workspace: Bitbucket workspace (optional if configured)'. This adds meaningful context beyond the bare schema, though it doesn't fully compensate for the lack of 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 tool's purpose: 'Get details of a specific pipeline.' It uses a specific verb ('Get') and resource ('pipeline'), but doesn't explicitly differentiate from sibling tools like 'list_pipelines' or 'get_pipeline_step_log'.

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_pipelines' for listing multiple pipelines or 'get_pipeline_step_log' for step-specific details, nor does it specify prerequisites or exclusions.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a 'Get' operation which implies read-only behavior, but doesn't confirm this explicitly. No information about authentication requirements, rate limits, error conditions, or what happens when parameters are invalid. The description mentions returns 'Step log content' but doesn't describe format, size limits, or potential truncation.

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 well-structured and appropriately sized. The purpose is stated clearly in the first sentence, followed by organized Args and Returns sections. No wasted words or redundant information. While efficient, the Args section could be slightly more detailed given the 0% schema coverage.

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 value documentation) but no annotations and 0% schema description coverage, the description does an adequate but minimal job. It explains what the tool does and what parameters mean, but lacks behavioral context that would be important for a read operation in a CI/CD context. The presence of an output schema reduces the burden, but more operational guidance 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?

Schema description coverage is 0%, so the schema provides no parameter documentation. The description adds basic semantic context for all 4 parameters, explaining what each represents (repository slug, pipeline UUID, step UUID, workspace). However, it doesn't provide format details, examples, or constraints beyond noting workspace is 'optional if configured'. The parameter explanations are minimal but cover all parameters.

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

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

The description clearly states the tool's purpose with 'Get the log output for a pipeline step' - a specific verb ('Get') and resource ('log output for a pipeline step'). It distinguishes itself from siblings like 'get_pipeline' or 'list_pipeline_steps' by focusing specifically on log retrieval rather than metadata. However, it doesn't explicitly differentiate from potential similar tools not in the sibling list.

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. While siblings include 'get_pipeline' and 'list_pipeline_steps', there's no indication of how this tool relates to them or when an agent should choose log retrieval over general pipeline/step information. The optional workspace parameter gets minimal explanation ('optional if configured'), but no broader usage context is provided.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states it's a read operation ('Get'), but doesn't mention authentication requirements, rate limits, error conditions, or what 'details' include. For a tool with no annotations, this leaves significant behavioral gaps, though it correctly indicates a read 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 well-structured and concise, with a clear purpose statement followed by separate Args and Returns sections. Every sentence earns its place, and there's no redundant information. It could be slightly more front-loaded with key details, but overall it's efficient.

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 (implied by 'Returns: Project details'), the description doesn't need to explain return values. However, with no annotations, 0% schema coverage, and 2 parameters, the description provides basic purpose and structure but lacks depth on usage, parameters, and behavior. It's minimally adequate but has clear gaps for effective 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 0%, so the description must compensate. It lists parameters in an 'Args' section, naming 'project_key' and 'workspace', but provides no semantic context—what a 'project key' is, how to find it, or what the 'workspace' parameter means. The description adds parameter names but minimal meaningful semantics beyond the bare schema.

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

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

The description clearly states the tool's purpose: 'Get details of a specific project' with a specific verb ('Get') and resource ('project'). It distinguishes itself from sibling tools like 'list_projects' by focusing on a single project rather than listing multiple. However, it doesn't explicitly contrast with 'create_project' or other project-related tools, keeping it at a 4 rather than a 5.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention when to use 'get_project' versus 'list_projects' or other project-related operations, nor does it discuss prerequisites or context for usage. The optional workspace parameter hint is minimal and doesn't constitute meaningful usage guidance.

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 details but does not describe authentication requirements, rate limits, error conditions, or whether it's a read-only operation (implied by 'Get' but not explicit). The mention of returned information is basic and lacks depth on format or completeness.

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 well-structured and front-loaded with the core purpose, followed by parameter and return details. It uses bullet-like sections ('Args:', 'Returns:') for clarity. However, the 'Returns' section could be more concise by integrating with the purpose statement, and some redundancy exists (e.g., repeating 'Pull Request').

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 parameters, no annotations, but with an output schema), the description is adequate but has gaps. It covers purpose and parameters but lacks usage guidelines, behavioral details, and error handling. The output schema existence reduces the need to detail return values, but the description should still address when and how to use the tool effectively.

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

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

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics: 'repo_slug' is clarified as 'Repository slug (name)', 'pr_id' as 'Pull Request ID', and 'workspace' as 'Bitbucket workspace (optional if configured)'. This provides essential context beyond the bare schema types, though it could elaborate on format expectations (e.g., slug conventions).

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 Pull Request on Bitbucket Cloud.' It specifies the verb ('Get details'), resource ('Pull Request'), and platform ('Bitbucket Cloud'), making the intent unambiguous. However, it does not explicitly differentiate from sibling tools like 'get_pull_request_activity' or 'get_pull_request_comments', which target specific aspects of pull requests rather than general details.

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 'list_pull_requests' for listing PRs or 'get_pull_request_activity' for activity logs, nor does it specify prerequisites such as authentication or workspace configuration. The optional 'workspace' parameter hint is minimal and lacks 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 mentions pagination parameters ('page', 'pagelen') and returns a list, but doesn't describe authentication requirements, rate limits, error conditions, or what specific event types are included beyond 'comments, approvals, and updates'. 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 well-structured and appropriately sized. The first sentence clearly states the purpose, followed by a parameter breakdown and return statement. Each sentence earns its place, though the 'Args:' and 'Returns:' formatting could be more integrated with the main description text.

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

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

Given the tool's moderate complexity (5 parameters, 2 required), 0% schema description coverage, no annotations, but with an output schema (implied by 'Returns: List of activity events'), the description is partially complete. It covers parameters well but lacks behavioral context and usage guidance. The output schema reduces the need to describe return values, but more context on authentication, errors, and sibling differentiation 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?

Schema description coverage is 0%, so the description must compensate. It provides clear explanations for all 5 parameters: 'repo_slug: Repository slug (name)', 'pr_id: Pull Request ID', 'workspace: Bitbucket workspace (optional if configured)', 'page: Page number for pagination (default: 1)', 'pagelen: Number of results per page, max 100 (default: 50)'. This adds substantial value beyond the bare schema, though it doesn't explain format constraints (e.g., what constitutes a valid 'repo_slug').

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 activity/timeline of a Pull Request including comments, approvals, and updates.' This specifies the verb ('Get'), resource ('activity/timeline of a Pull Request'), and scope ('comments, approvals, and updates'). However, it doesn't explicitly differentiate from sibling tools like 'get_pull_request_comments' or 'get_pull_request', which might overlap in functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'get_pull_request_comments' and 'get_pull_request' available, there's no indication of how this tool differs or when it's preferred. The description only states what it does, not when to use it.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions pagination defaults and limits ('max 100'), which is useful, but lacks critical details: authentication requirements, rate limits, error handling (e.g., invalid PR IDs), or whether it's a read-only operation (implied by 'Get' but not explicit). 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 well-structured and front-loaded with the core purpose, followed by organized sections for Args and Returns. Each sentence adds value: the first states the action, and the parameter explanations are necessary given low schema coverage. It avoids redundancy but could be slightly more concise by integrating pagination details into the main flow.

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

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

Given no annotations, 0% schema coverage, and an output schema present, the description does an adequate job. It covers parameters well and hints at returns ('List of comments with details'), but lacks full behavioral context (e.g., auth, errors). The output schema likely defines the return structure, so the description doesn't need to detail it further, but overall completeness is moderate due to missing operational guidelines.

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 0%, so the description must compensate. It adds meaningful context for all 5 parameters: explains 'repo_slug' as 'Repository slug (name)', 'pr_id' as 'Pull Request ID', clarifies 'workspace' as optional with a default, and details pagination behavior ('page' and 'pagelen' with defaults and max). This goes beyond the bare schema, providing practical usage insights, though it could note format specifics (e.g., numeric PR IDs).

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 ('comments from a Pull Request on Bitbucket Cloud'), making the purpose unambiguous. It distinguishes from siblings like 'get_pull_request' (which retrieves PR metadata) and 'list_commit_comments' (which targets commits rather than PRs), though it doesn't explicitly name these alternatives. The specificity is good but lacks explicit sibling differentiation.

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

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

No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a valid PR ID), contrast with similar tools like 'get_pull_request_activity' (which might include comments), or specify use cases (e.g., reviewing feedback). The description assumes the user knows when to fetch PR comments without offering 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 it mentions pagination parameters (page, pagelen), it doesn't describe authentication requirements, rate limits, error conditions, or what happens when the PR doesn't exist. For a read operation with zero annotation coverage, this leaves significant gaps in understanding the tool's behavior.

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

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

The description is appropriately sized and well-structured with clear sections (purpose, Args, Returns). Each sentence earns its place, though the 'Returns' section is somewhat redundant given the purpose statement. The information is front-loaded with the core purpose first.

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 (though not shown here), the description doesn't need to detail return values. However, for a tool with 5 parameters, 0% schema coverage, and no annotations, the description should provide more behavioral context about authentication, error handling, and usage scenarios 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?

With 0% schema description coverage, the description compensates well by documenting all 5 parameters in the 'Args' section, explaining their purposes and defaults. It clarifies that 'workspace' is optional if configured, and specifies constraints like 'max 100' for pagelen. This adds substantial value beyond the bare schema.

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

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

The description clearly states the tool's purpose: 'Get the list of commits in a Pull Request.' This is a specific verb ('Get') + resource ('commits in a Pull Request') combination. However, it doesn't explicitly differentiate from sibling tools like 'get_commit' or 'list_commits', which work on repositories rather than pull requests specifically.

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_pull_request_diff' or 'get_pull_request_activity' that might provide related information, nor does it specify prerequisites or contextual constraints for using this tool effectively.

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

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions the tool returns 'diff content as text', it doesn't describe important behavioral aspects like whether this is a read-only operation (implied but not stated), rate limits, authentication requirements, error conditions, or pagination for large diffs. The description provides basic output format but misses key 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 perfectly structured and front-loaded: purpose statement first, then organized parameter explanations, then return value. Every sentence earns its place - the opening statement defines the tool, the Args section documents parameters efficiently, and the Returns section clarifies output. No wasted words or redundancy.

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

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

Given the tool's moderate complexity (5 parameters, 2 required), 0% schema coverage, and presence of an output schema, the description does well but has gaps. The parameter documentation is excellent, and the output schema handles return values, but behavioral aspects (permissions, rate limits, error handling) are missing. For a read operation with no annotations, this is mostly complete but could benefit from safety/constraint information.

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 0% schema description coverage, the description fully compensates by explaining all 5 parameters in the 'Args' section. Each parameter gets clear semantic explanation: repo_slug as 'Repository slug (name)', pr_id as 'Pull Request ID', file_path with usage guidance, context_lines with default value, and workspace with configuration note. This adds substantial value beyond the bare schema.

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

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

The description clearly states the specific action ('Get the diff') and resource ('for a Pull Request'), distinguishing it from sibling tools like get_pull_request (which retrieves metadata) and get_commit_diff (which operates on commits rather than PRs). The phrase 'code changes' in parentheses provides additional clarity about what a diff contains.

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

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

The description provides clear context for when to use optional parameters ('recommended for large PRs'), but doesn't explicitly state when to use this tool versus alternatives like get_pull_request_diffstat (which shows summary statistics) or get_commit_diff (for commit-level diffs). It offers practical guidance but lacks explicit sibling differentiation.

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

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

No annotations are provided, so the description carries the full burden. It states this is a 'Get' operation, implying it's read-only, but doesn't disclose other behavioral traits like authentication requirements, rate limits, error conditions, or pagination. The description is minimal and doesn't provide enough context for safe and effective use.

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

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

The description is well-structured and appropriately sized. It front-loads the purpose in the first sentence, followed by clear 'Args' and 'Returns' sections. There's minimal waste, though it could be slightly more concise by integrating the parameter descriptions into the main text.

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

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

Given the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is partially complete. It covers the basic purpose and parameters but lacks behavioral context and usage guidelines. The output schema exists, so the description doesn't need to detail return values, but other gaps remain.

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 includes an 'Args' section that names and briefly describes the three parameters, adding meaning beyond the input schema (which has 0% description coverage). However, it doesn't explain parameter formats (e.g., what a 'repo_slug' looks like), constraints, or examples. With low schema coverage, this provides basic but incomplete compensation.

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 summary of files changed in a Pull Request with line counts.' It specifies the verb ('Get'), resource ('files changed in a Pull Request'), and output type ('summary...with line counts'). However, it doesn't explicitly differentiate from sibling tools like 'get_pull_request_diff' or 'get_commit_diffstat', which reduces 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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_pull_request_diff' (which might provide full diff content) or 'get_commit_diffstat' (which might be for commits rather than PRs). There's no context about prerequisites, timing, 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It indicates this is a read operation ('Check' and 'get'), implying it's non-destructive, but does not specify authentication requirements, rate limits, error conditions, or response format details beyond high-level content. It adds some context about what the status includes (conflicts, approvals, blockers) but lacks operational specifics.

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 well-structured and front-loaded with the core purpose in the first sentence. The 'Args' and 'Returns' sections are clearly separated, making it easy to scan. Every sentence adds value without redundancy, and the total length is appropriate for the tool's complexity.

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

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

Given the tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is reasonably complete. It explains the purpose, parameters, and return content at a high level. The presence of an output schema means the description doesn't need to detail return values extensively, but it could benefit from more behavioral context (e.g., authentication, errors) to fully compensate for the lack of annotations.

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 0%, so the description must compensate. It provides clear semantic explanations for all three parameters: 'repo_slug' as 'Repository slug (name)', 'pr_id' as 'Pull Request ID', and 'workspace' as 'Bitbucket workspace (optional if configured)'. This adds meaningful context beyond the bare schema, though it could include examples or format details (e.g., what a 'slug' looks like).

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 ('Check if a Pull Request can be merged') and the resource ('Pull Request'), distinguishing it from siblings like 'merge_pull_request' (which performs the merge) and 'get_pull_request' (which retrieves general PR info). The phrase 'and get merge status details' further clarifies the dual purpose of checking mergeability and retrieving detailed status.

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 it checks merge status, suggesting it should be used before attempting to merge a pull request. However, it does not explicitly state when to use this tool versus alternatives like 'get_pull_request' (which might include some status) or 'merge_pull_request' (which performs the merge), nor does it mention any 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. It states this is a read operation ('Get'), which implies non-destructive behavior, but doesn't disclose authentication requirements, rate limits, error conditions, or response format details. The description adds basic behavioral context but lacks depth 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 well-structured with clear sections (purpose, Args, Returns) and uses minimal sentences. Each part earns its place by providing essential information without redundancy. It could be slightly more concise by integrating the sections more fluidly, but overall it's efficient and 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?

Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is reasonably complete. It covers purpose, parameters, and return scope. The output schema exists, so the description doesn't need to detail return values. However, it could improve by adding more behavioral context (e.g., authentication) given the lack of annotations.

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 0%, so the description must compensate. It provides meaningful semantics for both parameters: 'repo_slug: Repository slug (name)' and 'workspace: Bitbucket workspace (optional if configured)'. This clarifies what each parameter represents and the conditional requirement for 'workspace', adding significant value beyond the bare schema.

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

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

The description clearly states the tool's purpose: 'Get detailed information about a specific repository.' It specifies the verb ('Get') and resource ('repository'), but doesn't explicitly differentiate from sibling tools like 'list_repositories' or 'get_workspace_details' that might provide related information. The purpose is clear but lacks 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?

The description implies usage context through the parameter descriptions (e.g., 'optional if configured'), but doesn't provide explicit guidance on when to use this tool versus alternatives like 'list_repositories' for broader listings or other 'get_' tools for specific repository components. Usage is implied rather than explicitly stated.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is a read operation ('Get details'), which implies it's non-destructive, but doesn't cover authentication needs, rate limits, error handling, or what happens if the snippet doesn't exist. This leaves significant 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 appropriately sized and front-loaded with the core purpose. The Args and Returns sections are structured clearly, though the 'Returns' part could be more specific (e.g., listing key metadata fields). There's minimal waste, but slight room for improvement in detail.

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

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

Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is somewhat complete. It covers the basic purpose and parameters, and the output schema handles return values, so it doesn't need to explain those. However, it lacks behavioral context and usage guidelines, making it adequate 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 0%, so the description must compensate. It adds meaning by explaining that 'snippet_id' identifies the snippet and 'workspace' is optional if configured, which clarifies beyond the schema's basic types. However, it doesn't detail format constraints (e.g., ID structure) or provide examples, leaving some ambiguity.

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 snippet.' This is a specific verb ('Get') and resource ('snippet'), making it easy to understand. However, it doesn't explicitly differentiate from sibling tools like 'list_snippets' or 'create_snippet,' 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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_snippets' for browsing snippets or 'create_snippet' for creating new ones, nor does it specify prerequisites or contexts 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 mentions pagination behavior ('page', 'pagelen') and the return format ('List of repositories and the user's permission level for each'), which adds some context. However, it lacks details on authentication needs, rate limits, error conditions, or whether the operation is safe (read-only) versus destructive.

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 well-structured and concise, with a clear purpose statement followed by organized sections for 'Args' and 'Returns'. Each sentence earns its place by providing essential information without redundancy, making it easy to scan 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 parameters, no annotations, but with an output schema), the description is fairly complete. It covers the purpose, parameters, and return values adequately. The output schema existence means the description doesn't need to detail return structures, but it could improve by addressing behavioral aspects like authentication or error handling.

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 includes an 'Args' section that documents all three parameters (workspace, page, pagelen) with meanings and defaults, compensating for the 0% schema description coverage. It clarifies that 'workspace' is optional for filtering, 'page' defaults to 1, and 'pagelen' has a max of 100 with a default of 25, adding significant value beyond the bare schema.

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

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

The description clearly states the tool's purpose: 'Get the current user's repository permissions.' It specifies the verb ('Get') and resource ('current user's repository permissions'), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_workspace_permissions' or 'get_user_profile', which could provide overlapping functionality.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, such as authentication requirements, or compare it to sibling tools like 'list_workspace_permissions' or 'get_user_profile' that might offer similar or related data. Usage context is implied but not stated.

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

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'public profile information,' which implies a read-only, non-destructive operation, but it doesn't clarify authentication requirements, rate limits, error conditions, or what specific fields are included in the profile. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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

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

The description is concise and well-structured, using a clear purpose statement followed by brief sections for 'Args' and 'Returns.' Every sentence adds value without redundancy. It could be slightly more front-loaded by integrating the parameter explanation into the main description, but overall it's 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 low complexity (one parameter) and the presence of an output schema (which handles return values), the description is moderately complete. It covers the basic purpose and parameter semantics but lacks usage guidelines and detailed behavioral context. With no annotations, it should provide more guidance on authentication or error handling to be fully adequate 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?

The description adds minimal semantics beyond the input schema. It explains that the 'username' parameter can be a 'Bitbucket username or UUID,' which provides context not in the schema (which has 0% description coverage). However, it doesn't detail format constraints, examples, or how to handle invalid inputs. With one parameter and low schema coverage, the description compensates slightly but not fully, aligning with the baseline.

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

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

The description clearly states the tool's purpose: 'Get a user's public profile information.' It specifies the verb ('Get') and resource ('user's public profile information'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_current_user' or 'get_user_permissions', which prevents a perfect score.

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

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_current_user' (which might retrieve the authenticated user's profile) or 'get_user_permissions' (which focuses on permissions rather than profile details). Without this context, an agent might struggle to choose the right tool in a given scenario.

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 read operation ('Get'), which implies non-destructive, but doesn't cover other aspects like authentication requirements, rate limits, error conditions, or what 'detailed information' entails. 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 appropriately sized and front-loaded: the first sentence clearly states the purpose, followed by structured 'Args' and 'Returns' sections. There's minimal waste, though the 'Returns' section is somewhat vague ('Workspace details') and could be more specific if not covered by an output schema.

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

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

Given the tool's moderate complexity (1 parameter, no annotations, but with an output schema), the description is partially complete. It covers the basic purpose and parameter semantics adequately, but lacks behavioral details (e.g., permissions, errors). The presence of an output schema reduces the need to explain return values, but overall, it could provide more context for safe and effective use.

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

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

The description adds meaningful context beyond the input schema: it explains that 'workspace' is a 'Bitbucket workspace slug' and notes it's 'optional if configured.' Since schema description coverage is 0% (the schema only defines the parameter type without descriptions), this compensates well by clarifying the parameter's purpose and default behavior, though it could specify what 'configured' means.

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 workspace.' It specifies the verb ('Get') and resource ('workspace'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'list_workspaces' or 'list_workspace_members,' which would require a more specific scope statement.

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

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

The description provides implied usage through the parameter note: 'optional if configured,' suggesting this tool is for retrieving details of a specific workspace, possibly defaulting to a configured one. However, it lacks explicit guidance on when to use this versus alternatives like 'list_workspaces' (for multiple workspaces) or other workspace-related tools, leaving some ambiguity for the 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions pagination and filtering, which is useful, but fails to cover critical aspects like rate limits, authentication needs, error handling, or whether it's a read-only operation. 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 appropriately sized and front-loaded with the core purpose, followed by structured parameter and return details. Every sentence adds value, such as clarifying defaults and limits, making it efficient without unnecessary verbosity.

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

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

Given the tool's moderate complexity, 5 parameters, no annotations, and an output schema present, the description is partially complete. It covers parameters well but lacks behavioral context like safety or performance traits. The output schema handles return values, so the description need not explain them, but overall completeness is adequate 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?

The description adds meaningful semantics beyond the input schema, which has 0% description coverage. It explains each parameter's purpose, such as 'repo_slug' as the repository name, 'workspace' as optional, and 'query' for filtering branches by name. This compensates well for the schema's lack of descriptions, though it could detail format constraints like slug 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 tool's purpose as 'List branches in a repository,' which is a specific verb+resource combination. However, it does not explicitly differentiate from sibling tools like 'list_commits' or 'list_tags,' which are also list operations on repository resources, so it misses full 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?

The description provides no guidance on when to use this tool versus alternatives. It lacks context on prerequisites, such as needing repository access, and does not mention sibling tools like 'list_tags' or 'list_commits' for different listing purposes, leaving the agent without usage direction.

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