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openhee

Jeju Humanities Tour MCP Server

by openhee
OverviewSchemaRelated ServersScoreDiscussions
Python

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool serves a distinct purpose: listing regions, getting spot details, and recommending courses. No overlap exists, so an agent can clearly select the correct tool.

    Naming Consistency5/5

    All tools follow a consistent verb_noun snake_case pattern: list_regions, get_spot, recommend_course. No deviations or mixed conventions.

    Tool Count5/5

    Three tools is well-scoped for a humanities tour server: regions, spots, and courses. Each tool earns its place without redundancy or excessive minimality.

    Completeness3/5

    Core operations are covered, but missing a tool to list spots within a region or list all courses. Agents may struggle to discover spots without a listing tool, creating a minor gap.

  • Average 4/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit 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 provided. The description implies a read-only query operation but does not disclose behavior for missing spots, error handling, or other side effects. Minimal disclosure beyond 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 four sentences in Korean, front-loaded with purpose, and every sentence adds value. No redundancy or wasted words.

    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 simplicity (1 param, no output schema), the description covers purpose, usage, and parameter. However, it lacks details on return value format or error behavior, leaving some gaps.

    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 description compensates by specifying the name parameter should be the exact or partial name from user utterance. This adds useful guidance beyond the 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 clearly states the tool retrieves detailed info about a specific tourist spot and provides example queries. However, it does not explicitly distinguish it from sibling tools beyond implying singularity.

    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 says when to use (user asks about a specific spot by name) with examples, but does not mention when not to use or mention alternatives like list_regions or recommend_course.

    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?

    The description mentions joining tables and returning one course ordered by sequence, but lacks details on selection logic (e.g., how the best course is chosen), permissions, side effects, or error handling. Since no annotations are provided, the description carries the full burden but only partially fulfills it.

    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 concise (4 sentences) and front-loaded: first sentence states purpose, second provides usage example, third distinguishes from sibling, fourth explains internal logic. No redundant information, though could be slightly more compact.

    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?

    For a recommendation tool with no annotations and no output schema, the description explains input and output (one course with spots in order) but omits details like output format, behavior when no matches, or how the single recommendation is selected. It is 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%, and the description only reiterates the parameter names (region, theme, max_hours) without adding format, constraints, or examples. Given the low coverage, the description should compensate but does not add meaningful semantics beyond the parameter names.

    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 recommends humanities tour courses based on region, theme, and time constraints. It distinguishes itself from the sibling tool 'get_spot' by specifying that this tool is for multi-spot courses, not single spots.

    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?

    Explicitly provides when to use (user asks for a course with region, theme, and time constraints) and when not to use (single spot inquiry should use get_spot). This clear differentiation helps the agent select the correct tool.

    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 full burden. It states 'no arguments' and implies a list retrieval, but does not describe any potential side effects, return format, or other behavioral traits. Adequate for a simple read-only operation.

    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?

    Three concise sentences, front-loaded with purpose, no redundancy or unnecessary information.

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

    Completeness5/5

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

    Given the tool's low complexity (no parameters, simple list), the description is complete. An output schema exists, so return values are documented elsewhere.

    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 tool has zero parameters and the schema coverage is 100%. The description confirms 'no arguments', which is consistent. Baseline for 0 parameters is 4.

    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: to list regions available for tours in Jeju Island, with example user queries. It distinguishes from sibling tools like get_spot (specific spots) and recommend_course (course recommendations).

    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 when-to-use guidance with example phrases, but does not explicitly mention when not to use or mention alternative tools for other queries.

    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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