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djanzu

pxt-anzu-diary-mcp

by djanzu

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools, add-note and get-note, are clearly distinct: one creates a diary entry and the other retrieves one. No overlap or ambiguity exists between them.

    Naming Consistency5/5

    Both tool names follow the same verb_noun pattern with a hyphen separator: add-note and get-note. This is fully consistent and predictable.

    Tool Count3/5

    With only 2 tools, the server feels borderline thin. While each tool has a clear purpose, the count is at the low end of what is considered reasonable for a domain-specific server.

    Completeness3/5

    The server covers create and get operations only, missing update, delete, and list functionality. These are notable gaps for a diary management server, though the core add/retrieve flow is present.

  • Average 3.3/5 across 2 of 2 tools scored. Lowest: 2.7/5.

    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

  • 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 burden of behavioral disclosure. It only says 'add' but does not mention validation, date format requirements, whether existing entries with the same date are overwritten, or what happens on success/failure. This is minimal for a mutation 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?

    The description is a single short sentence, which is concise and front-loaded. There is no wasted wording, though it is quite sparse. It earns its place by stating the tool's basic function.

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

    Completeness2/5

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

    The tool has no output schema, no annotations, and low schema coverage. For a mutation tool, the description should provide more context about return values, error behavior, or required formats. The current description is too thin to fully guide an agent in invoking the tool correctly.

    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 0%, and the description does not explain the parameters. The parameter names 'date' and 'content' are somewhat self-explanatory, but no format details (e.g., ISO date, content length) are provided. The description adds little over the raw schema.

    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 '日記を追加します' clearly states the action (add) and the resource (diary/note). Given the sibling tool 'get-note', it distinguishes the write operation from the read operation, though it doesn't explicitly contrast them.

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

    Usage Guidelines2/5

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

    No explicit guidance on when to use this tool versus get-note. The sibling name implies usage (add vs get), but the description lacks any context about prerequisites, alternatives, or conditions for use. Without annotation support, the agent gets no clear direction.

    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?

    No annotations are provided, so the description carries the full burden. It clearly indicates a read operation via '取得します' but does not disclose error behavior, output format, or side effects. For a simple retrieval tool, this is adequate but lacks specificity.

    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 with no filler, and the key information is front-loaded. It is appropriate for the simple tool.

    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 single-parameter retrieval tool, the description covers the essential purpose and parameter meaning. However, it does not mention edge cases like missing year entries or return format details, and there is no output schema to compensate.

    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?

    The description adds key semantic meaning by tying the 'year' parameter to the year of the diary to retrieve. Since the schema provides no description and the parameter is just an integer, this is essential clarification.

    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 uses a specific verb '取得します' (retrieves) with a clear resource '指定された年の日記' (diary of the specified year). It clearly distinguishes from the sibling add-note, which implies a write operation.

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

    Usage Guidelines2/5

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

    The description provides no explicit guidance on when to use this tool versus add-note. It only states what it does, without any context or exclusions, leaving the differentiation to be inferred from the tool names.

    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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