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Server Quality Checklist

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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool targets a distinct statistical dimension (gender/age, inpatient/outpatient, institution type, region) plus a search tool, with no overlap in purposes.

    Naming Consistency5/5

    All tools follow the consistent pattern 'hira_disease_<specific_dimension>', using snake_case uniformly.

    Tool Count5/5

    5 tools is well-scoped for a focused domain of disease statistics, covering core breakdowns without unnecessary bloat.

    Completeness4/5

    The set covers search and major statistical breakdowns, but lacks a tool for overall aggregated statistics (e.g., total counts) which could be useful.

  • Average 3.3/5 across 5 of 5 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 is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

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    }

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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?

    With no annotations provided, the description must fully disclose behavior, but it only implies a read operation. There is no mention of potential destructiveness, rate limits, authentication needs, or return format, leaving significant gaps for a tool with six parameters.

    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, front-loading the key information. It is concise but could include more detail without becoming verbose, such as clarifying the output or usage context.

    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?

    Despite good schema coverage, the description lacks completeness for a tool with no output schema and six parameters. It does not explain the returned data structure, pagination behavior, or any constraints beyond parameter defaults, leaving the agent underinformed.

    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 coverage is 100%, and each parameter has a description in the schema. The tool description adds no additional meaning beyond the schema, so the baseline score 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 retrieves HIRA disease statistics filtered by medical institution region, effectively distinguishing it from siblings like hira_disease_gender_age_stats. The verb 'Get' and resource 'HIRA disease statistics' are specific, and the region scope sets it apart.

    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. The description lacks explicit context, exclusions, or prerequisites, relying solely on the tool name for differentiation.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    With no annotations, the description must disclose behavioral traits. It only states 'Get statistics', implying read-only operation, but does not mention pagination, data limits, error handling, authentication, or data freshness. The description is insufficient to inform the agent of operational characteristics.

    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, efficient sentence with no wasted words. However, it lacks structure or front-loading of critical details. It earns a good score for brevity but could be more informative while remaining concise.

    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?

    Given no output schema and six parameters, the description is too minimal. It does not explain what the statistics look like, how institution type is categorized, or how results are structured. Compared to the sibling tools, it provides insufficient context for an agent to understand its full role.

    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 description coverage is 100%, so the baseline is 3. The tool description adds only the aggregation context ('by medical institution class/type') but does not provide new meaning beyond the schemas already provide. It meets the minimum for a fully described schema.

    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 action ('Get'), the resource ('HIRA disease statistics'), and the grouping dimension ('by medical institution class/type'). It differentiates from sibling tools like hira_disease_gender_age_stats or hira_disease_region_stats by specifying the unique aggregation method.

    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 main description provides no guidance on when to use this tool versus alternatives. It does not mention prerequisites, use cases, or when to avoid it. The only usage hint ('use hira_search_disease first if unknown') is buried in a parameter description, not in the tool-level description.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior2/5

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

    No annotations are provided, and the description does not disclose behavioral traits such as pagination limits, data freshness, or error handling for invalid codes. The description only states the basic purpose, leaving agents uninformed about important behaviors like output structure or rate limits.

    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 directly communicates the tool's core function with no extraneous words. It is well-structured and front-loaded.

    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?

    Given the complexity (6 parameters, no output schema), the description is minimal. It fails to explain the return format or how the output is structured, which is critical for an agent to use the tool effectively. The lack of output schema makes the description insufficiently complete.

    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 description coverage is 100%, so the baseline is 3. The tool description itself adds no additional meaning beyond what is already in the input schema parameter descriptions. The param details in the schema are sufficient.

    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 action ('Get'), the resource ('HIRA disease statistics'), and the distinguishing feature ('split by hospitalization and outpatient care'). This differentiates it from sibling tools like hira_disease_gender_age_stats which splits by gender/age.

    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 provides no explicit guidance on when to use this tool versus alternatives. However, the input schema parameter 'sickCd' includes a hint to use hira_search_disease first if unknown, which is helpful but not comprehensive.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • 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. It discloses the purpose but does not mention output format, pagination behavior, data freshness, rate limits, or any other operational traits. The description is minimal and lacks transparency about key behavioral aspects.

    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 two concise sentences, front-loaded with the action, and contains no redundant information. Every word serves a purpose.

    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?

    Given the complexity (6 parameters, no output schema, no annotations), the description is insufficient. It does not explain the return structure, pagination implications, or any constraints beyond the parameter defaults. A more complete description would include expected output or link to documentation.

    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 description coverage is 100%, so the schema already documents all parameters adequately. The description adds no further significant meaning beyond the schema; it only provides a high-level use case. A score of 3 reflects the baseline when schema carries the load.

    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 'Get' and the resource 'HIRA disease statistics by gender and age', and provides a specific use case ('Korean medicine lecture examples after finding a disease code'). It distinguishes itself from sibling tools which focus on other dimensions (in/out, institution type, region).

    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 explicitly states when to use the tool ('after finding a disease code') and implies a prerequisite step (search for disease code first, as noted in the parameter schema). While it does not list alternative tools, the context signals clearly differentiate this tool from siblings.

    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?

    With no annotations, the description carries the burden of behavioral disclosure. It adds the key default to Korean medicine (medTp=2) beyond what's in the schema, but does not mention other behavioral traits like pagination behavior, rate limits, or that the tool is read-only.

    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?

    Two sentences, zero waste. The description is concise and front-loaded with the core purpose, followed by the key default behavior.

    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 complexity (6 parameters, no output schema, no annotations), the description is adequate but not complete. It covers the purpose and a key default, but lacks context about return format, use cases, or relationship to sibling tools. The rich schema partially compensates.

    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 already provides full descriptions for all 6 parameters (100% coverage). The description adds minimal extra value beyond restating the default for medTp. Baseline 3 is appropriate since schema does the heavy lifting.

    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 searches HIRA disease names and codes. It distinguishes itself from sibling tools which are all statistics-focused, making its purpose distinct and easy to understand.

    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?

    No explicit guidance on when to use this tool versus the sibling stats tools. The usage is implied (search first, then possibly use stats), but the description does not provide any when-to-use or when-not-to-use context.

    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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