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YohanLiu

MCP JSONDiff Kel

by YohanLiu
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.5

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool has a distinct and clear purpose focused on JSON comparison.

    Naming Consistency5/5

    The tool name 'jsonDiff' follows a consistent pattern (camelCase) and clearly describes its function. Since there is only one tool, there are no inconsistencies to evaluate.

    Tool Count2/5

    A single tool is generally too few for most server purposes, as it limits functionality and may indicate an incomplete or overly narrow scope. For a JSON diff server, one tool might suffice for basic comparison, but it feels thin and lacks supporting operations.

    Completeness3/5

    The tool covers the core function of JSON comparison, which aligns with the server's name. However, there are notable gaps, such as missing tools for handling different diff formats, merging JSON, or validating JSON inputs, which could limit agent workflows.

  • Average 1.7/5 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

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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

  • Behavior1/5

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

    With no annotations provided, the description carries full burden for behavioral disclosure. '执行json对比' only states the action without revealing any behavioral traits: it doesn't indicate whether this is a read-only operation, what format the comparison results take, whether it modifies data, what happens on errors, or any performance characteristics. The description fails to provide essential context about how the tool behaves.

    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 extremely concise at just three characters in Chinese ('执行json对比'), which translates to 'performs JSON comparison.' While severely under-specified, it's not wordy or repetitive. Every character serves a purpose in stating the core function, making it maximally efficient in terms of word count.

    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?

    Given a tool with 2 required parameters, 0% schema description coverage, no annotations, and no output schema, the description is completely inadequate. '执行json对比' doesn't explain what the tool returns, how parameters should be formatted, what the comparison logic entails, or any error conditions. For a comparison tool with undocumented inputs and outputs, this minimal description leaves critical gaps.

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

    Parameters1/5

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

    The schema has 0% description coverage, meaning neither parameter has any documentation in the structured schema. The description '执行json对比' adds no information about what 'expectKey' and 'actualKey' parameters represent, their expected formats, or how they're used in the JSON comparison. With two required parameters completely undocumented, the description fails to compensate for the schema's deficiencies.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose2/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description '执行json对比' (performs JSON comparison) states a general action but lacks specificity about what resources or data are being compared. It doesn't explain what 'expectKey' and 'actualKey' represent in the comparison context. While it avoids being a tautology with the name 'jsonDiff', it remains vague about the exact nature of the comparison operation.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines1/5

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

    The description provides no guidance on when to use this tool, what scenarios it's designed for, or any prerequisites. There are no sibling tools mentioned, so differentiation isn't needed, but the complete absence of usage context makes it impossible for an agent to determine appropriate invocation conditions.

    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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