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webmoleai

mcp-vibe-check

by webmoleai
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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

    With only one tool, there is no possibility of confusion or overlap with other tools. The tool's purpose is clearly distinct by virtue of being the only tool in the server.

    Naming Consistency5/5

    A single tool name cannot have inconsistencies. The name 'vibe-check' is descriptive and follows a clear, if not standard, convention appropriate for its function.

    Tool Count4/5

    The server has a narrow, focused purpose—providing vibe checks on code. One tool is slightly below the typical 3-15 range, but it is perfectly reasonable for this specific, limited scope.

    Completeness5/5

    The tool covers the full stated purpose: assigning personality types, rating variable name energy, and suggesting aesthetic alternatives. There are no obvious missing operations within its defined domain.

  • Average 4/5 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
    • 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.

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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

  • Behavior3/5

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

    No annotations are present, so the description carries the full burden. It accurately discloses the tool's output behaviors (personality types, energy ratings, suggestions), but does not explicitly state whether it modifies code or is read-only. The word 'suggests' implies non-destructiveness, but it could be more transparent about side effects and return format.

    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, concise and well-structured. It front-loads the core purpose and elaborates with concrete details, with zero wasted text.

    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 simple one-parameter tool with no output schema, the description is mostly complete. It describes the input and the nature of the output (personality types, energy ratings, suggestions), though it could be slightly more explicit about the exact response format. Overall, adequate for the tool's complexity.

    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% with the parameter 'code' described as 'a snippet of code to vibe-check'. The description adds no extra semantics beyond this, so it meets the baseline but doesn't enrich parameter understanding.

    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 function with specific actions: assigns personality types, rates variable name energy, suggests alternatives. It's a specific verb+resource ('vibe check on code') and effectively distinguishes the tool's quirky purpose even without siblings.

    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 the tool (when you want a vibe check on your code). Since there are no sibling tools, no exclusions or alternatives are needed. The usage context is evident from the described actions.

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

GitHub Badge

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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