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cassiopeiaym

hermes-oh-my-pi-mcp

by cassiopeiaym
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Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools, 'doctor' and 'prompt', have clearly distinct purposes: one checks environment setup and the other runs the main functionality. There is no overlap or confusion between them.

    Naming Consistency3/5

    Both tool names are single words but do not follow a consistent verb_noun pattern. While simple and clear, they lack a predictable naming convention across the set.

    Tool Count3/5

    With only 2 tools, the server is at the lower boundary of acceptable size. For a simple one-shot execution server, this may be appropriate, but it feels thin compared to typical MCP servers.

    Completeness3/5

    The tool surface covers checking availability and executing the main command, but misses other potential operations like configuration or version info, leaving minor gaps for more complex agent workflows.

  • Average 3.2/5 across 2 of 2 tools scored. Lowest: 2.5/5.

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

    • No community issues in the last 6 months
    • 4 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.

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  ]
}

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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?

    Minimal disclosure: only mentions one-shot mode and result type. No details on side effects, authentication requirements, or parameter interactions. No annotations exist to compensate.

    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?

    Single sentence is concise, but it sacrifices necessary detail. It is not overly verbose but lacks structure for a tool with 7 parameters.

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

    Completeness1/5

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

    With 7 parameters, no output schema, and no annotations, the description is severely incomplete. It does not explain return format beyond 'text or JSON', nor cover optional parameters.

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

    Parameters2/5

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

    Schema coverage is 0%, but description only adds context for the required 'prompt' parameter. Other parameters like 'cwd', 'model', 'provider', etc. are left completely unexplained.

    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?

    Description names the tool (oh-my-pi) and specifies its action: running in one-shot mode and returning text or JSON. It is clear about what it does, though no differentiation from sibling tool 'doctor' is provided.

    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 the sibling 'doctor' or any other alternatives. The description does not mention any prerequisites or context for use.

    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?

    The description indicates a read-only diagnostic action ('Check'), which implies no side effects. However, with no annotations, it does not elaborate on potential behaviors like error handling, output format, or permission 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?

    The description is a single, front-loaded sentence that conveys the essential information without waste. Every word is purposeful.

    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 has no parameters, no output schema, and is a simple diagnostic check, the description sufficiently covers its functionality. No additional details are required.

    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 zero parameters, so the description does not need to add parameter meaning. Baseline of 4 applies as no param info is necessary.

    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 checks availability of 'oh-my-pi' and 'bun runtime', using a specific verb 'Check' and naming the resources checked. This distinguishes it from the sibling 'prompt' tool.

    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 (e.g., 'prompt'). It only states what the tool does without context on preconditions or selection criteria.

    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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