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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: listing codes, searching codes, getting full content for a code, and searching within a single document. No overlap or ambiguity.

    Naming Consistency5/5

    All tools follow the consistent 'kcsc_verb_noun' pattern with snake_case, e.g., kcsc_get_content, kcsc_list_codes, kcsc_search_codes, kcsc_search_sections.

    Tool Count5/5

    Four tools is well-scoped for a code/document lookup server, covering key operations without redundancy or deficiency.

    Completeness4/5

    The set covers listing, searching, and retrieving content for KCSC codes. A minor gap is the lack of a standalone 'list sections' or metadata-only endpoint, but search_sections partially addresses in-document navigation.

  • Average 3.4/5 across 4 of 4 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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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?

    Annotations already indicate read-only, non-destructive, idempotent behavior. The description adds that the tool supports optional filtering and pagination, which is consistent but not deeply informative. No contradiction.

    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 only one sentence, which is very concise and front-loaded with the key action and resource. It is appropriate in length, but could be slightly expanded without harming conciseness.

    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 presence of an output schema, the description does not need to detail return values. However, it does not mention pagination semantics or how filtering interacts with the list, which could be useful context. Adequate but not thorough.

    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%, so the tool description should compensate by explaining the parameters. It does not mention any of the four parameters (code_type, keyword, limit, offset), although the schema itself provides descriptions. The tool description adds no value to parameter understanding.

    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 action ('List') and resource ('available KCSC codes') with optional filtering and pagination. However, it does not differentiate from sibling tools like kcsc_search_codes, which might perform similar listing with different scope.

    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 guidance is provided on when to use this tool versus alternatives or when filtering is appropriate. The description lacks context about prerequisites or use cases.

    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?

    Annotations already declare readOnlyHint=true, idempotentHint=true. Description matches that but adds no additional behavioral context (e.g., rate limits, auth needs). Adequate but no extra value.

    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?

    Single sentence, no waste. Could be slightly more informative but is concise and front-loaded.

    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?

    Description doesn't mention optional filters (code_type, limit) or that it returns a list. However, output schema exists and annotations cover safety. Could be more complete but adequate for a simple search.

    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?

    Schema parameter descriptions are present and detailed (keyword required, code_type optional with values 'KCS'/'KDS', limit with range). Description adds no parameter info, but with high schema coverage, baseline 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?

    Description clearly states verb (search), resource (KCSC codes), and method (by keyword). It distinguishes from sibling tools like kcsc_list_codes and kcsc_search_sections, though not explicitly.

    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 guidance on when to use this tool vs alternatives. No mention of when not to use or context for selecting this over siblings like kcsc_list_codes or kcsc_search_sections.

    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?

    Annotations already declare readOnlyHint=true and idempotentHint=true, indicating a safe, read-only operation. The description adds no behavioral context beyond what annotations provide, such as rate limits or side effects. It does not contradict annotations.

    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 sentence that directly states the purpose. While concise, it is somewhat minimal but still clear. No wasted words.

    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 that the tool has an output schema and annotations covering safety and idempotency, the description is sufficiently complete for its simplicity. It does not explain return format, but that is handled by the output schema.

    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 input schema includes detailed descriptions for each parameter (e.g., 'Code type. Use 'KCS' or 'KDS'.'), so the description adds no additional parameter meaning. With schema coverage effectively high, a baseline score of 3 is appropriate.

    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 action ('search') and resource ('titles and contents inside a single KCSC document'). It distinguishes itself from siblings like 'kcsc_search_codes' which searches codes, and 'kcsc_get_content' which gets content.

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

    Usage Guidelines3/5

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

    The description does not provide explicit guidance on when to use this tool versus alternatives. It implies usage context (needs a KCSC document and code) but offers no exclusions or alternative recommendations.

    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?

    Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=true, so the description adds little beyond confirming the read-only nature. No additional behavioral traits like error handling or pagination are disclosed, but the description does not contradict annotations.

    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 that front-loads the action and resource. Every word is informative with no unnecessary fluff.

    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?

    The description states it fetches 'full document content', and since an output schema exists (though not displayed), it compensates for missing return value details. It does not mention error handling or invalid codes, but for a simple fetch tool, this 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 input schema provides thorough descriptions for all three parameters (code_type, code, plain_text), so the description adds no extra meaning. Schema description coverage is effectively high, meeting the baseline of 3.

    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 verb 'Fetch' and the resource 'full document content for a specific KCS or KDS code'. It distinguishes from sibling tools like kcsc_list_codes (listing codes) and kcsc_search_codes (searching), making the tool's purpose unambiguous.

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

    Usage Guidelines3/5

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

    The description implies usage when you have a specific code, but it does not explicitly state when to use this tool versus alternatives or provide any guidance on when not to use it. Minimal contextual cues are given.

    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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