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rabbit385

crypto-inspector-mcp

by rabbit385

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusing it with another. The single inspect_token tool has a clearly defined purpose, so an agent cannot misselect it.

    Naming Consistency4/5

    The only tool name follows a clear verb_noun convention (inspect_token) and accurately reflects its function. There is no set of tools to establish a broader naming pattern, but the name is well-formed and self-explanatory.

    Tool Count2/5

    The server exposes only one tool for what is described as a comprehensive security and liquidity check. This feels too thin for the as a token inspection MCP, which would typically benefit from separately callable tools for specific aspects such as liquidity details, holder analysis, or price data.

    Completeness2/5

    The tool surface is extremely limited, offering only a single monolithic action. While the description claims a comprehensive check, there are no additional tools for focused queries, comparing tokens, or retrieving specific aspects of the analysis, leaving obvious gaps in an inspection workflow.

  • Average 3.2/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 3 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
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  • 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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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 carries the full disclosure burden. The verb 'check' implies a read-only analysis operation, but the description does not disclose what specific checks are performed, whether external calls are made, whether the operation is safe and non-mutating, or what the result contains. The word 'comprehensive' promises breadth without specifying it — a meaningful gap for an inspection tool.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    A single 12-word sentence with zero filler. The core action is front-loaded and the structure is clean. It loses one point only because the brevity sacrifices informative content that would have helped behavioral transparency and contextual completeness.

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

    Completeness3/5

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

    The tool signature is simple — two well-documented parameters, one enum-constrained — so the schema carries most of the invocation burden. However, with no output schema and no annotations, the agent has no idea what a 'comprehensive security and liquidity check' returns or what criteria it evaluates. The vague 'comprehensive' leaves a notable gap given the absence of output documentation.

    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%: both contractAddress and chain are already documented, and chain has an enum restricting valid networks. The description adds no parameter-level meaning beyond the schema, which is acceptable given the high coverage baseline of 3.

    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 states a clear verb ('Perform'), a specific resource ('cryptocurrency token contract'), and the nature of the operation ('security and liquidity check'). It effectively communicates the tool's domain. However, the qualifier 'comprehensive' is vague — it does not enumerate what security or liquidity checks are actually performed — which keeps this from 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 Guidelines3/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    There are no sibling tools, so there is no need for exclusionary routing. The phrase 'security and liquidity check' implies the usage context of vetting a token before interacting with it, but no explicit when-to-use guidance is provided. The usage scenario is only implied, not stated.

    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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