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kmandana
by kmandana

Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: commit changes, create PR, get commit context, get PR context, and review changes. No overlaps in functionality.

    Naming Consistency5/5

    All tool names follow the verb_noun snake_case pattern consistently, e.g., commit_changes, get_commit_context, create_pr.

    Tool Count5/5

    With 5 tools, the server is well-scoped for assisting with git workflows without being overwhelming or insufficient.

    Completeness4/5

    Covers core workflow: commit, PR, context retrieval, and review. Missing staging or branch management, but these are minor gaps for the intended domain.

  • Average 4.6/5 across 5 of 5 tools scored. Lowest: 4/5.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior3/5

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

    No annotations exist, so the description bears full responsibility. It reveals that the tool returns a JSON string with commits, files, diff chunk, and pagination info, and explains the max_diff_tokens parameter. However, it does not state whether the tool is read-only or discuss side effects, authentication, or rate limits.

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

    Conciseness3/5

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

    The description is front-loaded with the core purpose, but the IMPORTANT section includes workflow instructions that go beyond tool behavior, adding length. While useful, it could be more concise. The parameter descriptions are clear and 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 (branches, diffs, pagination, token limits) and that an output schema exists, the description covers the main aspects: branch specification, pagination via cursor, token limit rationale, and return type. Missing details on error handling or prerequisites but adequate for the 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?

    With 0% schema description coverage, the description compensates by explaining all five parameters: base_branch, head_branch, cursor, max_diff_tokens, repo_path. It provides defaults, purpose (e.g., pagination cursor, token limit), and context (e.g., 'leaves room for commits/files in 25k limit').

    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 explicitly states 'Get diff and commits between branches for PR description,' clearly identifying the tool's action and target. It distinguishes from siblings like get_commit_context and review_changes, which serve different purposes.

    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 IMPORTANT section provides a step-by-step workflow for using the tool's output, guiding the agent on when to call it (for PR description generation) and how to proceed. It lacks explicit exclusions but offers clear context.

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

  • Behavior5/5

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

    With no annotations provided, the description fully bears the burden of behavioral disclosure. It reveals that only staged changes are shown, explains pagination (token-based, 25k limit), details the return structure (has_changes, files, secret_scan, diff, etc.), provides a step-by-step analysis guide including secret scanning, and clarifies behavior for edge cases (empty diff).

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

    Conciseness3/5

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

    The description is quite long and includes extensive step-by-step instructions that could be better placed elsewhere. While it front-loads the critical 'REQUIRED FIRST STEP' message, it could be more concise by separating behavior from workflow instructions.

    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 no annotations and a return structure described in the text, the description is complete: it covers all parameters, return fields, pagination, error handling (empty diff), security scanning, and even formatting rules for commit messages. No gaps remain for effective usage.

    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?

    The input schema has 0% description coverage, but the description's 'Args' section explains each parameter: cursor for pagination, max_diff_tokens for token limit, repo_path defaults to working directory. This adds meaningful context absent from the 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 'Get git diff and file changes to analyze before writing a commit message,' specifying the verb (get), resource (git diff and file changes), and purpose (analyze before commit). It distinguishes itself from sibling tools like 'commit_changes' by positioning itself as the required first step.

    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?

    Explicitly states 'REQUIRED FIRST STEP' and instructs the agent to never write a commit message without first seeing the diff. It also describes when to stop (empty diff) and what to tell the user. While it doesn't directly compare to alternatives, the strong directive provides clear usage context.

    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 describes the behavior: creates a PR, requires user approval, and returns a success message with URL or error. It mentions defaults (head_branch defaults to current branch, draft default False). It does not detail side effects like CI triggers, but the essential behavior is clear.

    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 critical workflow section and clear parameter explanations. It is somewhat long but every sentence is necessary for safe usage. Minor improvements could be made by condensing the workflow steps, but overall it's effective.

    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 (7 parameters, 4 required) and no annotations, the description is remarkably complete. It explains the workflow, each parameter's role, and the return value. It also addresses prerequisite context (get_pr_context) and user approval, leaving no critical 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%, but the tool description adds significant meaning for each parameter: e.g., 'title: PR title (keep it concise, ~50 chars)', 'user_approved: REQUIRED - Must be True.' This goes well beyond the bare schema titles.

    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: 'Create a pull request on the detected platform (GitHub/GitLab).' It uses a specific verb and resource, and distinguishes itself from siblings like commit_changes and review_changes.

    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 a detailed step-by-step workflow, explicitly stating when to use the tool (only after user approval) and when not to (not in the same response as generating the description). It also names a prerequisite tool (get_pr_context) and includes critical warnings.

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

  • Behavior5/5

    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 fully explains the requirement for user approval, the execution of the commit, and the expected return (success message with commit hash or error). It also warns not to call the tool prematurely, ensuring safe usage.

    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 the purpose, then provides a critical numbered workflow, followed by parameter details and return value. It is slightly verbose due to explicit step-by-step instructions, but every sentence is meaningful and earns its place.

    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?

    The description is comprehensive for the tool's complexity: it covers the workflow, parameters, and return value. Although an output schema is not provided in the data (context says 'Has output schema: true' but no schema shown), the description concisely states 'Returns: Success message with commit hash or error,' which is sufficient for a straightforward commit operation.

    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?

    The description adds significant meaning beyond the input schema: it specifies that the message should follow the 50/72 rule, clarifies that user_approved must be True and represents user consent, and explains that repo_path is optional and defaults to Claude's working directory. This compensates for the 0% schema description coverage.

    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 'Execute git commit with a user-approved commit message,' specifying the action (commit), resource (git), and the key condition (user-approved). It is distinct from sibling tools like get_commit_context (diff retrieval) and create_pr (pull request creation).

    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 a detailed, step-by-step workflow that must be followed exactly, including calling get_commit_context first, generating and showing a commit message to the user, obtaining approval, and only then invoking this tool with user_approved=True. It explicitly states 'DO NOT call this tool in the same response where you generate the commit message,' providing clear guidance on 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.

  • Behavior5/5

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

    No annotations provided, but description fully discloses behavior: returns JSON with summary, changes, diff, context clues, etc. Explains how to interpret and present results. No contradictions.

    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?

    Very detailed and well-structured with clear sections, but quite lengthy. Every section adds value, but could be more concise while retaining essential 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?

    Covers all aspects: purpose, when to call, prerequisites, parameters, output schema (explained even though output schema exists), and how to present results. Complete for a tool with 3 parameters and output schema.

    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%, but description includes an 'Args:' section that explains each parameter (goal, scope, repo_path) with defaults and usage guidance, adding significant meaning beyond the 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?

    Clearly states the tool reviews code changes before staging/committing. Provides specific verb 'review' and resource 'code changes', and distinguishes from sibling tools like commit_changes and create_pr.

    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?

    Explicitly states WHEN TO CALL: after making changes and before staging/committing. Gives required prerequisite to provide a 'goal' summary. Provides detailed instructions on how to present the response.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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