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tosssssy

debug-thinking

by tosssssy
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TypeScript
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Server Quality Checklist

67%
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  • Latest release: v0.1.3

  • Disambiguation5/5

    Only one tool exists, so there is no ambiguity between tools. The tool's multiple actions are clearly separated within it.

    Naming Consistency5/5

    The single tool name 'debug_thinking' is consistent and descriptive. No naming inconsistencies exist.

    Tool Count5/5

    One tool is appropriate for this domain as it encapsulates all necessary operations (create, connect, query) in a cohesive interface for debugging knowledge management.

    Completeness4/5

    The tool covers core actions like creating nodes, connecting them, and querying. Missing explicit update/delete operations for nodes, but the graph-based approach may rely on recreation.

  • Average 4.9/5 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 is failing

  • This repository is licensed under MIT License.

  • 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

  • Behavior5/5

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

    Without annotations, the description fully discloses behavior: it maintains a graph, persists data to ~/.debug-thinking-mcp/, and describes the effects of each action (create, connect, query). No contradictions.

    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 well-organized: purpose sentence, usage guidelines, bullet-pointed actions, example workflow, and persistence note. Front-loaded and every section adds value without redundancy.

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

    Completeness5/5

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

    Given the tool's complexity (11 params, nested objects, no output schema, no siblings), the description explains the graph concept, all actions, when to use, and provides a complete example. No gaps for effective use.

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

    Parameters4/5

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

    Schema coverage is 100%, so baseline is 3. The description groups parameters by action and provides an example workflow, adding context beyond the schema. However, it does not delve deeper into each parameter's semantics beyond what the schema 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 it is a 'Graph-based debugging knowledge management system' that helps track debugging systematically and retrieve past solutions. It lists specific actions (CREATE, CONNECT, QUERY) with details, making the purpose unambiguous. No siblings exist to differentiate from.

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

    Usage Guidelines5/5

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

    Explicitly provides 'Use this tool when:' conditions: error reporting, need to document approach, check past solutions, build knowledge base. Also includes an example workflow demonstrating how to use the actions in sequence.

    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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