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curtis-d-williams

mcp-policy-guardian

by curtis-d-williams
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Python
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Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.4

  • Disambiguation5/5

    Only one tool exists, so there is no possibility of confusion between tools.

    Naming Consistency5/5

    The single tool name 'check_repo_policy' follows a clear verb_noun pattern, consistent with itself.

    Tool Count3/5

    One tool is minimal but may be acceptable for a very narrow single-purpose server. However, given the server name 'Policy Guardian', a broader set of policy management tools would be expected.

    Completeness2/5

    The tool only checks for standard repository governance artifacts. There are no tools for applying policies, reporting, or managing exceptions, leaving significant gaps for a policy guardian server.

  • Average 3.7/5 across 1 of 1 tools scored.

    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 is passing

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  • This repository includes a README.md file.

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

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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

  • Behavior5/5

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

    Despite no annotations, the description explicitly states key behaviors: deterministic, network-free, read-only, and fail-closed. It also lists stable output keys, providing transparency about what the tool returns. This fully compensates for missing annotations.

    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?

    Extremely concise: three short sentences covering purpose, constraints, and output keys. No redundant information, front-loaded with the key message.

    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?

    For a one-parameter tool with no siblings, the description covers purpose, constraints, and output structure. It lacks detail about what specific artifacts are checked, but the stable keys and behavior hints provide enough context for an agent to use it correctly.

    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 sole parameter 'repo_path' is not described in the description, leaving its format and semantics implicit. However, the parameter name is self-explanatory given the tool's purpose, and the schema provides the type. With 0% schema coverage, some description would be better, but the parameter is simple.

    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 identifies the tool as a deterministic check for standard repository governance artifacts. It specifies the action (check) and resource (repo policy) with enough specificity, though the exact artifacts could be elaborated.

    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. The description does not mention prerequisites, contexts, or exclude inappropriate uses. With no sibling tools, the omission is less critical but still a gap.

    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 there are no obvious security issues.
  • Evaluate tool definition quality.

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