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keeganthewhi

tenth-man-mcp

by keeganthewhi
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Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool serves a distinct purpose: configuration, history query, and triggering a review. There is no ambiguity or overlap between them.

    Naming Consistency5/5

    All tool names follow the same pattern: 'tenth_man_' followed by a verb (configure, history, review). This is consistent and predictable.

    Tool Count5/5

    With only 3 tools, the server is tightly scoped to its core functionality (configure, review, history). This is appropriate for a focused protocol like the 10th Man.

    Completeness4/5

    The tools cover the essential lifecycle: configuration, triggering a review, and querying history. A minor gap is the lack of a tool for approval or execution plan creation, but these are described as manual steps outside the tool surface.

  • Average 3.9/5 across 3 of 3 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
    • No stable releases found
    • 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.

  • Add a glama.json file to provide metadata about your server.

  • 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

  • Behavior2/5

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

    No annotations are provided, so the description alone must disclose behavioral traits. While it lists configuration goals, it omits important details such as whether changes persist, require restart, or affect ongoing operations. The description is insufficient for a configuration tool.

    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 two sentences with no wasted words. It front-loads the purpose and provides a useful auto-detection note. Every sentence 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?

    With no output schema and no annotations, the description covers the essential configuration aspects. It explains what can be configured and mentions auto-detection. It could mention return value or persistence, but for a lightweight configuration tool it is reasonably complete.

    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 100% with each parameter having a clear description. The tool description maps parameters to categories ('preferences, timeouts, trigger patterns'), adding context but not significant new meaning beyond the schema. Baseline 3 is appropriate.

    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?

    Description states 'Configure agent preferences, timeouts, and trigger patterns for the 10th Man Protocol.' It uses a specific verb ('configure') and resource ('10th Man Protocol settings'), clearly distinguishing from sibling tools like 'tenth_man_history' and 'tenth_man_review'.

    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 changing settings, but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. The line 'Auto-detects available CLI agents if not specified' offers some context but no formal guidelines.

    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?

    No annotations provided, so description carries full burden. It discloses return content (verdicts, issues, agents) but doesn't mention if read-only, side effects, or authentication requirements. Bare minimum.

    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?

    Single sentence is concise and directly conveys purpose. No unnecessary words.

    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?

    With no output schema, description adequately summarizes return values (verdicts, issues, agents). Lacks mention of pagination or limits, but last_n parameter covers count. Good for a simple query tool.

    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 coverage is 100%, so baseline 3. Description does not add extra meaning beyond the schema's parameter descriptions (e.g., last_n, filters). No compensation needed.

    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 'Query', the resource 'past 10th Man audit reports', and what it returns. It distinguishes from siblings by focusing on history retrieval vs configuration or review.

    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 its siblings (tenth_man_configure, tenth_man_review) or when not to use it. The description only states what it does.

    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?

    Discloses key traits: spawns 3 agents, 2-5 minute duration, parallel vs sequential execution, standard vs auto mode behaviors, and required post-approval step. No annotations provided so description carries full burden; missing auth or rate limit details but still strong.

    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?

    Five well-structured sentences with bullet points, no wasted words. Front-loaded purpose, then usage, then behavioral details. Every sentence earns 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 six parameters (four required), two enums, no output schema, and no annotations, the description covers purpose, usage, modes, time estimate, and post-action steps comprehensively. Leaves no critical gaps.

    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 coverage is 100% (baseline 3). Description adds value by explaining severity levels in context (e.g., 'high = 3+ files cross-module') and mode semantics beyond enum values.

    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 triggers the 10th Man Protocol with 3 contrarian agents, using specific verbs and resource. It distinguishes from sibling tools (tenth_man_configure and tenth_man_history) which are for configuration and history, respectively.

    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?

    Provides explicit usage scenarios (3+ file cross-module, architecture, auth/security, data model, costly mistakes) and explains standard vs auto modes. Lacks explicit when-not-to-use but sibling tools imply this is the sole review action.

    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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Glama performs regular codebase and documentation scans to:

  • 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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