Commit Helper MCP

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation2/5
Multiple tools have overlapping purposes that could cause confusion. For example, generate_commit_message and create_commit_message both generate commit messages with similar parameters, while get_git_status and get_enhanced_git_status provide overlapping repository status information. Tools like commit_workflow_step, generate_and_commit, and stage_files_and_commit all handle commit execution workflows with unclear boundaries between them.
Naming Consistency4/5
Most tools follow a consistent snake_case verb_noun pattern (e.g., analyze_repository_health, get_branch_analysis, validate_commit_message). There are minor deviations like commit_workflow_step (which mixes verb_noun_step) and health_check (which uses verb_noun without underscore), but overall the naming is predictable and readable.
Tool Count2/5
With 21 tools, this server feels overloaded for a commit helper domain. Many tools could be consolidated (e.g., the multiple commit message generators and status checkers). The high count creates cognitive overhead without clear justification for each tool's distinct existence in the workflow.
Completeness5/5
The tool surface provides comprehensive coverage of the commit workflow domain. It includes analysis tools (repository health, branch analysis, diff analysis), message generation and validation tools, status checking tools, configuration management, and multiple commit execution pathways. There are no obvious gaps - agents can analyze, prepare, validate, and execute commits through various workflows.
Average 3.5/5 across 21 of 21 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'state management' and returns 'workflow state and next step information', but doesn't disclose critical behavioral traits like whether this performs actual Git operations, requires authentication, has side effects, or handles errors. For a tool with 'commit' in its name and complex workflow logic, 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized with a brief overview followed by Args and Returns sections. It's front-loaded with the core purpose, though some sentences could be more informative. No wasted text, but the content is under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given complexity (multi-step workflow with state management), no annotations, and an output schema (which handles return values), the description is incomplete. It outlines the tool's role but lacks details on behavior, error handling, or integration with sibling tools. The output schema reduces burden, but key contextual gaps remain for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 basic meaning by explaining 'workflow_data' as 'Workflow state data' and 'step' with enum values, but doesn't detail the structure of 'workflow_data' or how steps transition. With 2 parameters and nested objects, this provides minimal semantic value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it's a 'Multi-step commit workflow with state management' which gives a general purpose, but it's vague about what specific action it performs. It doesn't clearly distinguish from sibling tools like 'execute_git_commit' or 'stage_files_and_commit' that also handle commit operations. The verb 'commit' in the name isn't elaborated in the description beyond workflow management.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives is provided. With many sibling tools related to commits (e.g., 'execute_git_commit', 'preview_git_commit'), the description doesn't explain this tool's specific role in the workflow or when to choose it over others. Usage is implied through parameter descriptions 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'comprehensive analysis' and lists analysis components but doesn't disclose behavioral traits like whether this is a read-only operation, performance characteristics, data returned format beyond 'Dict', error conditions, or any limitations. For a tool with no 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a clear opening statement, bulleted list of analysis components, and separate Args/Returns sections. It's appropriately sized at 7 lines. The front-loaded purpose statement earns its place, though the bulleted list could be slightly more concise. Overall efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 1 parameter with 0% schema coverage and no annotations, the description provides basic purpose and parameter semantics. The output schema exists (though unspecified here), so return values needn't be detailed. However, for a comprehensive analysis tool with many sibling alternatives and no behavioral transparency, the description is minimally adequate but lacks usage guidance and deeper behavioral context that would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 the Args section explaining 'repo_path: Path to git repository', which gives basic semantics for the single parameter. However, it doesn't specify format expectations (absolute vs relative path, existence requirements) or examples. With 1 parameter and partial documentation, this meets the baseline but doesn't fully compensate for the schema gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'comprehensive repository health analysis using GitPython features' and lists specific analysis components like statistics, commit frequency, branch/tag info, file changes, and author contributions. This is specific (verb+resource) and distinguishes it from siblings focused on commits, messages, or status checks rather than holistic health analysis. However, it doesn't explicitly contrast with similar siblings like 'health_check' or 'get_branch_analysis'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools for commit analysis, branch analysis, and status checks, there's no indication of when this comprehensive health analysis is preferred over more targeted tools. The description implies usage through its content but offers no 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.
Behavior2/5
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 the tool 'analyzes' and 'helps organize' changes, which suggests a read-only or advisory function, but doesn't clarify if it modifies the repository, requires specific permissions, has side effects, or handles errors. For a tool with no annotations, this leaves significant gaps in understanding its behavior and safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: it starts with a clear purpose statement, followed by a helper sentence, then parameter details, and a return statement. Each sentence adds value without redundancy. However, the parameter section could be more integrated into the flow rather than a separate list, slightly affecting structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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, no annotations, and an output schema present, the description is moderately complete. It explains the tool's purpose and parameters but lacks behavioral context and usage guidelines. The output schema handles return values, so the description doesn't need to detail them. However, for a tool with no annotations and incomplete parameter semantics, it should do more to guide safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 with brief explanations: 'repo_path: Path to git repository', 'file_groups: List of file groups with metadata', and 'generate_messages: Whether to generate commit messages for each group'. This adds meaning beyond the schema's property titles, but details like 'file_groups' metadata structure or 'repo_path' format are unspecified. The description partially compensates but doesn't fully cover the gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze multiple file groups for batch commit operations' and 'Helps organize staged changes into logical commit groups with appropriate commit messages for each group.' It specifies the verb ('analyze') and resource ('multiple file groups'), distinguishing it from siblings like 'execute_git_commit' or 'stage_files_and_commit'. However, it doesn't explicitly differentiate from similar analysis tools like 'get_branch_analysis' or 'smart_commit_suggestion' beyond the batch focus.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools for commit-related operations (e.g., 'execute_git_commit', 'generate_commit_message', 'smart_commit_suggestion'), there's no indication of prerequisites, context (e.g., after staging files), or comparisons. The description implies usage for organizing changes but doesn't specify when this analysis is needed over other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool generates a commit message and returns a dict with message and validation status, but lacks details on permissions, rate limits, error handling, or whether it's read-only or mutative. 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose clearly, followed by structured Args and Returns sections. There's no wasted text, but the formatting with quotes and line breaks could be slightly cleaner for direct readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (one parameter with nested objects), no annotations, and an output schema present, the description is partially complete. It covers the basic purpose and parameter intent, but lacks context on integration with siblings (e.g., dependency on 'get_commit_questions'), behavioral traits, and error scenarios, 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds some meaning beyond the input schema: it specifies that 'answers_dict' is a 'Dictionary containing all answers to commit questions', which clarifies its purpose and content. However, with 0% schema description coverage and only one parameter, this provides basic context but doesn't detail structure, required fields, or examples, leaving room for improvement.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate a commit message from a complete answers dictionary.' It specifies the verb 'Generate' and the resource 'commit message', and distinguishes it from siblings like 'generate_commit_message' by mentioning the input format. However, it doesn't fully differentiate from 'smart_commit_suggestion' or 'generate_and_commit' in terms of scope or context.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal guidance: it implies usage when you have a 'complete answers dictionary', but offers no explicit when-to-use vs. alternatives like 'generate_commit_message' or 'smart_commit_suggestion'. There's no mention of prerequisites, such as needing to call 'get_commit_questions' first, or exclusions for other contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 the return type ('Dict containing the questions and metadata'), which adds some behavioral context, but fails to disclose key traits like whether it's read-only, requires authentication, has rate limits, or what 'interactive' implies (e.g., user input needed). This is inadequate 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: one stating the purpose and another specifying the return type. It's front-loaded with the main function, and each sentence adds value without waste. However, it could be slightly more structured by integrating the return info into the first sentence for better flow.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, and an output schema exists (implied by 'Returns'), the description is somewhat complete. It covers the purpose and return type, but lacks context on when to use it among siblings and behavioral details like interactivity requirements. For a simple retrieval tool, this is minimally adequate but has clear gaps in guidance and transparency.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there's no need for parameter details in the description. The baseline for zero parameters is 4, as the description doesn't need to compensate for any gaps. It appropriately avoids redundant parameter information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool 'Get interactive questions for commit message generation,' which clarifies its purpose as retrieving questions. However, it's vague about what 'interactive questions' entail and doesn't differentiate from siblings like 'get_commit_types' or 'smart_commit_suggestion,' which might also provide guidance for commits. It avoids tautology by not just restating the name, but lacks specificity in distinguishing its role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description doesn't mention context, prerequisites, or exclusions, such as whether it's for initial commit setup or iterative refinement. With siblings like 'create_commit_message' and 'generate_commit_message,' the lack of usage guidelines leaves the agent unsure of when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 tool validates against rules but doesn't disclose behavioral traits such as what validation entails (e.g., format checks, rule compliance), error handling, or performance aspects. This is a significant gap for a validation 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.
Conciseness4/5
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 no wasted text, and it efficiently conveys core information in a few lines.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (validation with plugin rules), no annotations, and an output schema present, the description is partially complete. It covers the basic action and parameter but lacks details on validation rules, error cases, or output structure. The output schema mitigates some gaps, but more context on behavior would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds minimal semantics: it names the parameter ('message') and indicates it's 'The commit message to validate.' With 0% schema description coverage and 1 parameter, this provides basic meaning beyond the schema's title ('Message') and type. However, it doesn't elaborate on format, constraints, or examples, leaving gaps in understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Validate an existing commit message against the current plugin's rules.' It specifies the verb (validate), resource (commit message), and context (plugin's rules). However, it doesn't explicitly differentiate from siblings like 'validate_commit_readiness' or 'preview_git_commit', which might have overlapping validation aspects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to commits (e.g., 'create_commit_message', 'execute_git_commit', 'validate_commit_readiness'), there's no indication of prerequisites, timing, or comparisons. The context is implied (validating against plugin rules) but lacks explicit usage instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'reinitialize the service,' hinting at a mutation/restart action, but doesn't disclose critical behavioral traits like whether this is safe, idempotent, requires specific permissions, or has side effects (e.g., downtime). For a mutation tool with zero annotation coverage, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
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 and return details in the second. However, the second sentence could be omitted since an output schema exists, slightly reducing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 0 parameters, 100% schema coverage, and an output schema, the description is minimally adequate. However, for a mutation tool ('Refresh' implies change) with no annotations, it should do more to explain behavioral context (e.g., side effects, safety), making it incomplete for confident agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so no parameter information is needed. The baseline for 0 parameters is 4, as the description doesn't need to compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Refresh') and target ('Commitizen configuration'), and mentions reinitializing the service, which provides a specific verb+resource. However, it doesn't explicitly distinguish this tool from its many siblings (like health_check or get_git_implementation_info), 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.
Usage Guidelines2/5
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., when configuration might be stale) or exclusions, leaving the agent to infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions using GitPython and analyzing staged changes, but doesn't disclose critical behavioral traits: whether this is a read-only operation, if it modifies the repository, what permissions are needed, or any rate limits. The description is functional but lacks transparency about the tool's operational characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and well-structured. It starts with a clear purpose statement, then details what the tool analyzes, lists parameters with brief explanations, and specifies the return type. Each sentence adds value without redundancy. The front-loaded purpose statement makes the tool's function immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (4 parameters, no annotations, but has output schema), the description is partially complete. It covers the basic purpose and parameters but lacks behavioral transparency and usage guidelines. The presence of an output schema means the description doesn't need to explain return values, but it should address when to use this tool versus siblings and disclose operational characteristics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate for the schema's lack of parameter documentation. It successfully adds meaning by listing all four parameters ('repo_path', 'analyze_changes', 'suggest_type', 'suggest_scope') and briefly explaining their purposes in the context of commit suggestions. This provides essential semantic context beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Intelligent commit message suggestions based on repository changes.' It specifies the verb ('suggest') and resource ('commit message'), and mentions using GitPython to analyze staged changes. However, it doesn't explicitly differentiate from sibling tools like 'create_commit_message' or 'generate_commit_message', which appear to have similar functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to commits (e.g., 'create_commit_message', 'generate_commit_message', 'execute_git_commit'), there's no indication of when this 'intelligent' suggestion tool is preferred over others. It mentions analyzing staged changes but doesn't specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions 'validation' and describes the return format, it doesn't explain what validation entails, what validation failures look like, whether the tool has side effects, or any rate limits or authentication requirements. The description provides some behavioral context but 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections (purpose statement, Args, Returns) and uses bullet-like formatting. Every sentence serves a purpose, though the parameter explanations could be slightly more concise. The structure 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (7 parameters, no annotations, but with output schema), the description provides good coverage. It explains the tool's purpose, documents all parameters with semantics, and describes the return format. With an output schema present, it doesn't need to detail return values further. The main gap is lack of usage guidance relative to sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for 7 parameters, the description compensates well by listing all parameters with brief explanations of their purpose. Each parameter gets a clear semantic description (e.g., 'type: The commit type (e.g., 'feat', 'fix', 'docs')'), which adds significant value beyond the bare schema. The only gap is that it doesn't explain parameter interactions or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate a commit message with validation using provided parameters.' This specifies the verb (generate with validation) and resource (commit message), though it doesn't explicitly differentiate from sibling tools like 'create_commit_message' or 'validate_commit_message' which appear to serve similar functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools related to commit messages (create_commit_message, validate_commit_message, generate_and_commit, etc.), there's no indication of this tool's specific use case or how it differs from similar tools in the server.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 returns a dict with health information, which is helpful, but lacks details on what the health check entails (e.g., uptime, errors, dependencies), whether it requires authentication, or if it has rate limits. For a tool with no annotations, this is a significant gap in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise and well-structured: it starts with the core purpose in one sentence and follows with a brief note on the return value. There's no wasted text, and it's front-loaded with the main action, making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has 0 parameters, 100% schema coverage, and an output schema exists (implied by 'Returns: Dict'), the description is somewhat complete. However, for a health check tool with no annotations, it could benefit from more detail on what the health information includes or typical use cases. The output schema likely covers the return structure, but the description doesn't fully compensate for the lack of behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 the schema fully documents the lack of inputs. The description doesn't need to add parameter information, and it correctly doesn't mention any parameters, aligning with the schema. This meets the baseline for tools with no parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 the health and status of the Commitizen service.' This specifies the verb ('Check') and resource ('Commitizen service'), making it understandable. However, it doesn't explicitly distinguish it from sibling tools like 'analyze_repository_health', which might have overlapping health-checking aspects but focuses on repositories rather than the service itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, timing (e.g., for diagnostics or monitoring), or how it differs from other health-related tools in the sibling list, such as 'analyze_repository_health'. This leaves the agent without clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 tool provides 'comprehensive branch analysis' and lists information types, but doesn't disclose behavioral traits like whether it's read-only, potential performance impacts, error conditions, or how it handles large repositories. The description adds some context about what information is returned but lacks critical 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and appropriately sized. It starts with a clear purpose statement, bullet-points key information provided, then separately documents args and returns. Every sentence earns its place with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (branch analysis), no annotations, 0% schema coverage, but with an output schema present, the description is reasonably complete. It explains what the tool does and what information it provides, and the output schema will handle return value details. However, it lacks operational context that would be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaningful semantics for the single parameter: 'repo_path: Path to git repository'. With 0% schema description coverage and only one parameter, this adequately compensates by explaining what the parameter represents. However, it doesn't provide format examples or validation rules beyond the basic definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 comprehensive branch analysis using GitPython' with specific details about what information is provided (local/remote branches, relationships, commit counts, last activity). It distinguishes from siblings by focusing on branch analysis rather than commits, status, or health checks, though it doesn't explicitly contrast with similar tools like 'analyze_repository_health'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 this tool is appropriate compared to siblings like 'get_git_status', 'analyze_repository_health', or 'get_detailed_diff_analysis', nor does it specify prerequisites or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 returns a dict with commit types and descriptions, which is helpful, but doesn't cover other aspects like whether it's a read-only operation (implied by 'Get'), potential errors (e.g., if no plugin is active), performance characteristics, or side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded: the first sentence states the purpose, and the second clarifies the return format. Every sentence earns its place with no wasted words, making it easy for an agent to parse quickly. The structure is clear and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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, output schema exists), the description is reasonably complete. It explains what the tool does and what it returns, which is sufficient for a basic read operation. However, with no annotations and many sibling tools, it could benefit from more context about when to use it or error conditions, but the output schema likely covers return values, reducing the burden on the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to explain parameters, so it appropriately focuses on the return value. This meets the baseline of 4 for zero-parameter tools, as there's no parameter information to add beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 list of available commit types from the current plugin.' This specifies the verb ('Get'), resource ('list of available commit types'), and source ('from the current plugin'). However, it doesn't explicitly differentiate from sibling tools like 'get_commit_questions' or 'get_git_implementation_info' that also retrieve information but about different resources.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 a plugin must be loaded), context for usage (e.g., before generating commit messages), or exclusions. With many sibling tools for commit-related operations, this lack of differentiation leaves the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 what the tool returns but doesn't cover key aspects like error handling (e.g., what happens if the repo_path is invalid), performance considerations, or whether it requires specific git configurations. This leaves gaps in understanding how the tool behaves in edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded, starting with a clear purpose statement followed by organized sections for Args and Returns. Every sentence adds value without redundancy, making it easy to scan and understand quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter) and the presence of an output schema (implied by the Returns section), the description is reasonably complete. It covers the purpose, parameter, and return values adequately. However, without annotations, it could benefit from more behavioral context, such as error handling or usage prerequisites.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 'repo_path: Path to git repository', which clarifies the parameter's purpose beyond the schema's basic title. However, it doesn't provide details like format examples (e.g., absolute vs. relative paths) or constraints, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 current git repository status and staged files.' It specifies the verb ('Get') and resource ('git repository status and staged files'), making the function evident. However, it doesn't differentiate from sibling tools like 'get_enhanced_git_status', which might offer more detailed status information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'get_enhanced_git_status' and 'get_detailed_diff_analysis', it's unclear if this is a basic status check or if other tools should be preferred for more comprehensive analysis. No context or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'comprehensive validation' and outlines return values, but lacks details on permissions, rate limits, error handling, or what 'validation' entails (e.g., checks for uncommitted changes, merge conflicts). This is a significant gap for a validation 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the purpose, followed by structured Args and Returns sections. Every sentence earns its place with no wasted words, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (validation with one parameter), no annotations, and an output schema (implied by the Returns section), the description is mostly complete. It covers purpose, parameters, and return structure, but lacks behavioral context like error cases or performance characteristics, which holds it back from a 5.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 0%, but the description compensates by documenting the single parameter 'repo_path' in the Args section, adding meaning beyond the bare schema. However, it doesn't specify format details (e.g., absolute vs. relative path, existence requirements), preventing a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
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 'Comprehensive validation of repository readiness for commit,' which is a specific verb (validate) + resource (repository readiness for commit). However, it doesn't explicitly distinguish this from sibling tools like 'validate_commit_message' or 'preview_git_commit,' which reduces the score from a perfect 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to commits (e.g., 'execute_git_commit,' 'validate_commit_message'), there's no indication of context, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 adds context about GitPython features and the types of information returned (e.g., file status, commit history, analytics), which helps understand the tool's behavior beyond basic status retrieval. However, it doesn't cover aspects like performance, error handling, or dependencies, leaving gaps in transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose followed by bullet points for details and parameter/return sections. Every sentence adds value, but the bullet points could be slightly more concise. Overall, it's well-structured with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (enhanced status retrieval), no annotations, and an output schema present (so return values needn't be explained), the description is fairly complete. It covers the purpose, features, parameter, and return type adequately. However, it lacks details on error cases or integration with sibling tools, leaving room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 explicitly documents the single parameter 'repo_path' as 'Path to git repository', adding clear meaning beyond the schema's minimal title. With only one parameter, this is sufficient, though it could provide more details like format examples or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool 'gets enhanced git repository status with detailed information', specifying the verb 'get' and resource 'git repository status'. It distinguishes from the sibling 'get_git_status' by emphasizing 'enhanced' and 'detailed information', though it doesn't explicitly contrast them. The purpose is specific but could be more explicit about differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'get_git_status' or other sibling tools. It mentions using GitPython features 'when available', which hints at prerequisites, but lacks explicit when/when-not instructions or named alternatives. Usage context is implied but insufficient for clear decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses key behavioral traits: the tool can generate messages and optionally execute commits, includes a safety mechanism ('preview_only: default for safety'), and mentions partial implementation ('stage_all: not implemented yet'). However, it doesn't cover permissions, error handling, or rate limits, leaving some 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and front-loaded with purpose, followed by detailed sections. It's appropriately sized for a complex tool but includes some redundancy (e.g., 'Returns' section could be more concise). Every sentence adds value, though minor trimming is possible.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (10 parameters, mutation capability, no annotations), the description is mostly complete. It explains parameters thoroughly, includes a 'Returns' section (though an output schema exists), and covers key behaviors. However, it lacks explicit prerequisites (e.g., git setup) and doesn't fully differentiate from all sibling tools, leaving minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 a detailed 'Args' section explaining all 10 parameters with semantics beyond schema titles (e.g., 'type: Commit type (feat, fix, docs, etc.)', 'preview_only: If True, only preview (default for safety)'). This adds significant value over the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Generate commit message and optionally execute commit in one step.' It specifies the verb ('generate and commit'), resource ('commit message'), and distinguishes from siblings like 'create_commit_message' (only generates) and 'execute_git_commit' (only executes) by combining both operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for usage: 'Combines message generation with git operations for streamlined workflow.' It implies when to use (for streamlined workflows) but doesn't explicitly state when NOT to use or name specific alternatives among the many sibling tools (e.g., 'create_commit_message' for generation only, 'execute_git_commit' for execution only).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does well by disclosing behavioral traits: it specifies the use of GitPython, lists analysis features (file-by-file changes, line-level counts, etc.), and mentions optional diff content inclusion. However, it doesn't cover aspects like error handling, performance, or authentication needs, which could be relevant for a tool with 3 parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded, starting with the core purpose, followed by a bulleted list of features and clear parameter/return sections. Every sentence adds value without redundancy, making it efficient and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (3 parameters, no annotations, but with an output schema), the description is mostly complete: it covers purpose, features, parameters, and returns. However, it lacks details on error cases or example usage, which could enhance completeness for a tool with moderate complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 for all 3 parameters: 'repo_path' as the repository path, 'compare_with' as the commit/branch to compare with (including default), and 'include_content' as a boolean for diff content inclusion. This goes beyond the schema's basic titles, though it could provide more detail on format or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 specific verbs ('get detailed diff analysis') and resources ('between working directory and specified commit'), distinguishing it from siblings like 'get_git_status' or 'get_branch_analysis' by focusing on detailed diff analysis rather than status or branch-specific analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for detailed diff analysis but does not explicitly state when to use this tool versus alternatives like 'get_enhanced_git_status' or 'preview_git_commit'. It lacks explicit guidance on exclusions or prerequisites, leaving usage context somewhat vague.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 key behavioral traits: the tool performs staging and committing operations, includes a safety feature ('dry_run: Preview only (default True for safety)'), and mentions sign-off behavior. However, it lacks details on permissions, error handling, or what 'results' entail in the return dict.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is appropriately sized and front-loaded: the first sentence states the core purpose, the second provides usage context, and the Args/Returns sections are structured efficiently. Every sentence adds value without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 does well by explaining all parameters and mentioning a return dict. However, with an output schema present, it doesn't need to detail return values, but could better address behavioral aspects like error cases or side effects for a mutation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 for all 5 parameters: explains 'files' as 'List of file paths to stage', 'message' as 'Commit message to use', 'repo_path' as 'Path to git repository', 'sign_off' as 'Whether to add sign-off to commit', and 'dry_run' as 'Preview only'. This goes beyond schema titles, though it doesn't detail formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Stage specific files and commit with provided message') and distinguishes it from siblings by emphasizing selective commits. It explicitly mentions 'Useful for selective commits of specific files,' which differentiates it from batch or automated commit tools 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.
Usage Guidelines4/5
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 ('Useful for selective commits of specific files'), but does not explicitly state when not to use it or name specific alternatives from the sibling list. It implies usage for targeted file commits without detailing exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by specifying the return structure in detail. It discloses that this is a read-only informational tool (implied by 'Get information'), though doesn't mention potential side effects, performance characteristics, or authentication requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Perfectly structured with a clear purpose statement followed by detailed return format. Every sentence adds value: the first states what it does, the second explains what it returns. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a 0-parameter tool with output schema (implied by the detailed return description), this description is complete. It explains both the purpose and the return values thoroughly, making the tool's behavior fully understandable without needing additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0 parameters and 100% schema description coverage, the baseline is 4. The description correctly indicates no parameters needed by not mentioning any, which aligns perfectly with the empty input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and resource 'information about the current git implementation and available features'. It distinguishes from sibling tools like 'get_git_status' or 'get_branch_analysis' by focusing on implementation metadata rather than repository state or analysis.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when needing to check git availability and capabilities, but doesn't explicitly state when to use this vs alternatives like 'health_check' or 'refresh_configuration'. No exclusions or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly discloses key behavioral traits: it's a non-executing preview ('dry-run mode'), mentions that 'stage_all' is 'not implemented yet', and describes the return structure. This adds valuable context beyond basic functionality, though it could detail more about validation rules or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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. It efficiently uses bullet points for Args and Returns, with each sentence adding clear value—no wasted words. The format enhances readability and quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity, no annotations, and an output schema that details return values, the description is complete enough. It covers purpose, parameters, and behavioral context (e.g., dry-run, unimplemented feature), aligning well with the structured data to provide a holistic understanding without redundancy.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
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 for all parameters: explains 'message' as the commit message, 'repo_path' as the repository path, notes 'stage_all' is not implemented, and clarifies 'sign_off' default and purpose. This goes beyond the schema's basic titles, though it could provide more on parameter interactions or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action: 'Preview git commit operation without executing (dry-run mode).' It explicitly distinguishes this from actual execution tools like 'execute_git_commit' among siblings, making the purpose distinct and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by specifying it's a 'dry-run mode' for previewing commits, which suggests it should be used before actual commits. However, it does not explicitly state when to use this tool versus alternatives like 'execute_git_commit' or other sibling tools, leaving some guidance implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden and does so effectively. It discloses safety mechanisms (requires force_execute=True), user approval needs, and behavioral traits like dry-run vs. actual execution. It also notes that 'stage_all' is 'not implemented yet', adding useful context about limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections for safety, args, and returns, making it easy to parse. It is appropriately sized with no redundant sentences, though the 'Args' and 'Returns' sections could be slightly more integrated into the flow. Every sentence adds value, earning its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a git commit tool with safety mechanisms and no annotations, the description is complete. It explains the tool's behavior, parameters, and return values in detail. With an output schema present, it doesn't need to elaborate on return types, but it still provides a clear summary, making it fully adequate for the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
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 fully. It adds significant meaning beyond the schema by explaining each parameter's purpose, defaults, and constraints (e.g., 'stage_all' not implemented, 'force_execute' as safety flag). This provides clear semantics for all 5 parameters, compensating for the lack of schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Execute actual git commit') with safety mechanisms and distinguishes it from siblings like 'preview_git_commit' and 'stage_files_and_commit'. It explicitly mentions the safety requirement for actual execution, making the purpose distinct and well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit guidance on when to use this tool: it requires 'force_execute=True' to perform an actual commit, implying it should be used for final execution after safety checks. It distinguishes from alternatives like 'preview_git_commit' (for dry runs) and other analysis tools, offering clear context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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