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Server Quality Checklist

67%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Both tools have entirely distinct purposes: one generates a book from markdown, the other searches materials. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tool names follow a consistent verb_noun (or verb_noun_preposition) pattern using snake_case, making them predictable and readable.

    Tool Count2/5

    With only 2 tools, the server feels under-scoped for a tutor. Expected tools like listing books, deleting, or retrieving specific books are missing, making the surface thin.

    Completeness2/5

    The tool set covers generation and search but lacks basic CRUD operations like listing, updating, or deleting materials. Important operations for managing a book collection are absent.

  • Average 4/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 9 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
  • This repository is licensed under MIT License.

  • 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 states the search and sort behavior, but lacks details such as whether the search is case-sensitive, if it supports partial matches, pagination, or any system limits. For a search tool, more transparency about result ordering and scope is expected.

    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 sentence in Korean that conveys all necessary information without any extraneous words. It is front-loaded and efficient, appropriate for a simple search 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?

    Given the tool has only one required parameter, no annotations, and an output schema (though not described here), the description is mostly complete. It covers the core function and ordering. However, it does not elaborate on the output format or whether multiple matches are returned, but the presence of an output schema likely handles that. For a straightforward tool, completeness is adequate.

    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 has 100% coverage (only one parameter) but description coverage is 0% (no param description in schema). The description adds that the query parameter is searched for in the title, which provides basic semantic meaning. However, it does not specify format, allowed characters, or whether the query is a single term or phrase. This is a minimal improvement over the schema alone.

    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 the tool searches for accumulated materials by title containing a query term, sorted by latest. It includes a specific verb (find/search), resource (accumulated materials), scope (title contains search term), and ordering (latest). This distinguishes it from the sibling tool generate_book_from_markdown, which creates materials rather than searching.

    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 implies the tool should be used when you need to find materials by their title with results in latest order. It does not explicitly state when not to use it or mention alternatives, but given only one sibling (generate), the context is clear enough. No exclusionary or conditional guidance is provided.

    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 explains the output formats and the expected markdown structure, but does not disclose behavioral traits such as error handling, whether the tool is idempotent, or any side effects. It adds some value beyond the schema but lacks depth in behavioral disclosure.

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

    Conciseness3/5

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

    The description is lengthy due to the markdown writing rules, which could be restructured or shortened. While it is front-loaded with the key usage instruction, the bulk of text may hinder quick comprehension. It is adequately structured but not maximally concise.

    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?

    Given the tool has an output schema (exists), the description does not need to explain return values. It covers the main usage, parameter semantics, and content requirements. However, it does not mention error conditions or what happens if input is invalid, which keeps it from being fully complete.

    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 0%, so the description must explain parameters. It does so for 'output_format' by detailing each format's meaning (pdf for print, html for web, markdown as source). For 'markdown_content', it provides detailed writing rules specifying the required chapter structure. Only 'topic_title' lacks additional explanation, but the overall compensation is strong.

    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 the tool's purpose: generating a book from markdown content. It explicitly says it is the primary tool for textbook creation, and the verb 'generate' combined with 'book from markdown' precisely identifies the resource and action.

    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?

    The description provides explicit usage guidance: it instructs the agent to use this tool first for textbook generation, and crucially tells the agent to ask the user for the output format if not specified. It also explains when to avoid defaulting, which is excellent contextual instruction.

    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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