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mtakahashi-ivi

project-decision-rag

by mtakahashi-ivi
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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 confusion or misselection. The tool has a unique, clearly defined purpose.

    Naming Consistency5/5

    The single tool name 'find_project_decisions' follows a clear verb_noun pattern and is internally consistent.

    Tool Count2/5

    A single tool feels too thin for a server named 'project-decision-rag'. Even a focused RAG server would typically include additional tools for managing or indexing decisions.

    Completeness2/5

    The server only provides search/retrieval of project decisions. There is no way to add, update, or delete decisions, which are significant gaps for a decision management workflow.

  • Average 3.7/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 6 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

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden. It implies a read-only search but doesn't disclose return format, behavior when no rules match, or whether it performs semantic/vector search. The description is not misleading, but it lacks behavioral details beyond the basic purpose.

    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, concise sentence in Japanese that front-loads the action ('searches') and clearly states the scope ('project-specific'). There is no redundant or unnecessary information.

    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?

    Given the tool has only one parameter, no annotations, and no output schema, the description is somewhat minimal. It explains purpose and usage but lacks details about the result structure or how the agent should interpret the returned decision rules. This is an adequate but not fully complete description for a search tool.

    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 already covers 100% of the parameter description, stating 'query' is the question or situation for which to search decision rules. The tool description adds no further semantic detail beyond what the schema provides, so the baseline of 3 is appropriate.

    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 searches for project-specific decision rules related to the user's question. It specifies the verb 'search' and the resource 'decision rules', and distinguishes itself from general knowledge by emphasizing project-specificity. However, there are no sibling tools to differentiate, so it doesn't explicitly contrast with alternatives.

    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 clear usage context: use this tool when project-specific rules should take precedence over general knowledge. This helps the agent decide when to invoke it, though no explicit alternatives or exclusions are mentioned.

    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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