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molpass

tojeong-mcp

by molpass

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one takes a birthdate and produces the year's fortune, the other accepts a gwae code for direct retrieval. The descriptions explicitly delineate user-facing use vs. development/testing, so an agent would not confuse them.

    Naming Consistency4/5

    Both tools share the 'tojeong_' prefix and use snake_case, which is consistent. However, the second part differs in pattern: 'fortune' is a noun while 'gwae_lookup' is a compound noun+verb, creating a minor inconsistency.

    Tool Count3/5

    With only two tools, the server feels thin for a fortune service, but the scope is narrow and both tools serve specific purposes. It falls in the borderline range for tool count.

    Completeness4/5

    The server covers the core workflow of obtaining a Tojeong fortune from a birthdate, with an additional low-level lookup. It intentionally omits interpretation/advice, so within its data-only scope the surface is sufficient, though a tool to return just the gwae code might be a minor gap.

  • Average 4.3/5 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

  • Behavior3/5

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

    With no annotations, the description bears the transparency burden. It discloses that the lookup returns the exact original text ('그대로 조회') and is auxiliary, implying read-only intent. But it does not mention permissions, return format, error behavior, or side effects, leaving some behavioral aspects unspecified.

    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 sentences long, front-loading the core functionality and then stating the intended purpose. Every clause contributes meaning without redundant repetition of schema information.

    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 simple single-parameter lookup with no output schema, the description adequately covers input format, what is returned (yearly and monthly fortune text), and intended usage. It does not detail response structure or the exact relationship with tojeong_fortune, but given the tool's simplicity and auxiliary role, this is sufficient.

    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 schema already covers the parameter with a pattern and example (100% coverage), but the description adds valuable meaning by explaining the code structure ('상1-8·중1-6·하1-3') and range (111~863), which is more intuitive than the regex pattern and aids correct parameter construction.

    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 states a specific action '조회한다' (retrieves) and a specific resource (the hexagram's total fortune and 12-month monthly fortune original text) using a code format. It also distinguishes itself as an auxiliary tool for browsing/testing/SKILL development, separating it from the sibling tojeong_fortune.

    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 clearly identifies intended contexts ('browsing, testing, SKILL development') via '보조 도구다'. However, it does not explicitly state when not to use the tool or name the alternative tojeong_fortune, so it lacks explicit exclusions.

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

  • Behavior5/5

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

    With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently explains the internal procedure (작괘), the output content (총운 and 12-month monthly fortune), the fact that it returns original text unchanged, and that it does not generate interpretations or use the hour. This is a thorough and honest account of the tool's behavior.

    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 concise and well-structured: three sentences each serve a distinct purpose—stating the main function, describing the method and return value, and clarifying exclusions. It is front-loaded with the core purpose and contains no redundant words or information.

    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 tool with no output schema and no annotations, the description does a good job of explaining what it returns and what it does not do. It covers the essential behavior and exclusions effectively. However, it does not mention parameter defaults (e.g., target_year defaults to current year) or provide any guidance relative to the sibling tool, which would round out the context. Nevertheless, the description is sufficiently complete for typical use.

    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?

    Since the schema description coverage is 100%, all parameters (birth_date, calendar, target_year, is_leap_month) already have clear descriptions. The tool description adds minimal extra meaning: it confirms birth_date as the key input and explicitly states that the hour is not used, which is a helpful clarification but does not significantly go beyond the schema. Therefore, baseline 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 purpose: it inquires the annual Tojeong Secret fortune based on birth date, computes a 3-digit hexagram, and returns the overall and monthly fortunes as original text. It distinguishes itself from the sibling tool by specifying its input (birth date) and output (fortune text), making it unambiguous.

    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 usage context: it is a data-only tool that returns raw original text and does not generate interpretations or advice, which serves as an exclusion criterion. It also notes that the hour is not used, guiding the user on relevant inputs. However, it does not explicitly mention alternatives like the sibling tool tojeong_gwae_lookup, so it falls short of a full 'when-to-use-vs-alternatives' explanation.

    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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