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Server Quality Checklist

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  • Latest release: v1.1.0

  • Disambiguation5/5

    The two tools address entirely different verification domains: one assesses transaction risk for x402/MCP resources, while the other evaluates the veracity of factual claims. There is no overlap in inputs, operations, or outputs, making misselection impossible.

    Naming Consistency4/5

    Both tool names use lowercase and avoid special characters, but verify_transaction follows a clear verb_noun pattern while factcheck is a single compound word. This minor stylistic mismatch is easy to read and does not hinder predictability.

    Tool Count3/5

    With only two tools, the server feels somewhat thin. However, each tool covers a distinct, substantive verification use case, and the narrow focus justifies the small count, making it acceptable if not ideal.

    Completeness4/5

    The server's implied domain is pre-action verification, and the two tools cover the primary needs: verifying transactions and verifying facts. No critical gaps are apparent within this scope, though a broader verification suite might include other resource types.

  • Average 3.9/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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
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  • 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?

    With no annotations, the description carries the full burden of behavioral disclosure. It adds a useful detail about the live x402 challenge controlling price, but it does not clarify whether the tool has side effects or requires special permissions. The safety profile is missing, so a score of 3 is appropriate.

    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 consists of two concise sentences, front-loaded with the tool's purpose. Every sentence adds value with 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?

    For a simple one-parameter tool with no output schema, the description covers the purpose, usage context, and return categories (risk, recommendation, evidence). It lacks detailed return structure, but the simplicity of the tool makes the description sufficiently 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?

    The schema fully covers the 'url' parameter with a clear description. The tool description repeats the context but adds no new parameter semantics. Schema coverage is 100%, so the baseline of 3 applies.

    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 states the tool returns risk, recommendation, and evidence for unknown resources before payment. It uses a specific verb and resource context (x402/MCP resource), but it does not explicitly distinguish from sibling 'factcheck', so it falls just short of a 5.

    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 a clear condition for use: 'Before paying an unknown x402/MCP resource'. This is explicit context, but it does not mention alternatives or exclusions, so it earns a 4 rather than a 5.

    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?

    There are no annotations, so the description carries the full burden of behavioral disclosure. It does reveal the return structure (verdict, confidence, primary sources, freshness, contradictions, evidence) and implicitly indicates a non-mutating, read-only operation ('verify'). However, it does not disclose potential details like rate limits, authentication requirements, error behavior, or side effects, which could be relevant for an agent invoking the 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 a single sentence that front-loads the purpose and then lists the key output components. There is no filler or redundant information. Every phrase contributes to understanding the tool's function and result.

    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, the description compensates by enumerating the return fields, which is helpful. However, it does not explain the semantics of the 'depth' options or how to populate the 'context' object, leaving gaps for a tool with nested parameters and no annotations. Overall, it covers the essential purpose and outputs but misses some operational details.

    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 description coverage is only 33% (only 'claim' has a description). The tool description does not explain the 'depth' parameter (quick/standard/deep) or the 'context' object and its fields, which are undocumented in the schema. While the description refers to 'factual claim,' it adds no semantic detail about how to use these parameters beyond what the schema already provides.

    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: 'Verify a factual claim before acting on it.' This provides a specific verb ('verify') and resource ('factual claim'), and it distinguishes itself from the sibling tool 'verify_transaction' by focusing on factual claims rather than transactions. The mention of return values (verdict, confidence, primary sources, etc.) further clarifies the purpose.

    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 phrase 'before acting on it' gives a clear context for when to use the tool — whenever a factual claim needs verification prior to making a decision or proceeding. However, it does not explicitly mention when not to use it or mention alternatives like 'verify_transaction'. The context is clear but exclusions are absent.

    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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  • Evaluate tool definition quality.

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