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wtfsayo

user-review-mcp

by wtfsayo
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Server Quality Checklist

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

  • Latest release: v0.7.7

  • Disambiguation5/5

    With only one tool, there is no ambiguity between tools. The tool's purpose is clearly described.

    Naming Consistency5/5

    The single tool uses a consistent verb_noun pattern ('get-user-review'), though with only one tool, consistency is trivial.

    Tool Count2/5

    A single tool for user reviews seems too few. A more complete set would include tools for creating, listing, or updating reviews.

    Completeness2/5

    Missing obvious operations like submitting a review, listing reviews, or getting specific reviews. The current tool only retrieves a review, which is insufficient for a full review workflow.

  • Average 3.6/5 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?

    Without annotations, the description should disclose behavioral traits. It hints that the tool provides 'honest, critical feedback' and implies a human reviewer, but it doesn't specify whether the review is synchronous, if there are delays, or any required permissions. The description is vague about the mechanics.

    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 moderately concise with multiple sentences and a bulleted list. Each part adds value, but it could be tightened without losing meaning. Not excessively long, but not extremely efficient.

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

    Completeness2/5

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

    Missing important details: no mention of what the tool returns (string, object, etc.), whether the review is instant or queued, or any prerequisites. With 2 parameters and no output schema, the description should cover these aspects for completeness.

    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 clear descriptions for both parameters. The tool description adds usage context (e.g., 'after significant work') but doesn't significantly enhance parameter understanding beyond the schema. Baseline 3 for high 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 the tool's action ('Get a user review') and resource ('the work that was completed'). It also elaborates on the purpose: connecting with a user reviewer for feedback on work. No sibling differentiation needed as no siblings are listed.

    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 explicit guidance on when to use the tool with three bullet points (after completing significant work, when needing feedback, to validate implementation). It lacks explicit when-not-to-use or alternatives, but given no siblings, this is sufficient.

    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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