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wangsquirrel

divination-chart-mcp

by wangsquirrel
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.2

  • Disambiguation5/5

    Two tools cover distinct divination methods (bazi vs liuyao); descriptions clarify their differences, so no confusion.

    Naming Consistency5/5

    Both tools follow the same 'divination_' prefix plus descriptive type name in snake_case, ensuring predictable pattern.

    Tool Count4/5

    Two tools is appropriate for a niche domain focused on specific chart types; slightly low but not unreasonable.

    Completeness4/5

    Covers two major Chinese divination methods; could include others like ziwei but current scope is coherent and sufficient.

  • Average 3.1/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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 is passing

  • 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 that the tool returns 'detailed information and insightful analysis' but does not disclose whether it is read-only, destructive, requires authentication, or has rate limits. There is no mention of data handling or side effects, leaving behavioral traits unclear.

    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, concise sentence in Chinese (about 30 characters) that efficiently states the purpose and inputs. It is front-loaded with the tool's function. However, it could potentially include more structured information like usage context without sacrificing brevity.

    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 of Bazi chart calculation, the description is insufficient for an AI agent unfamiliar with the concept. It does not explain what Bazi is, how the analysis is derived, or provide any background needed for correct selection. The existence of an output schema mitigates return value explanation, but the description still lacks necessary context for an informed choice.

    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 description coverage is 100%, meaning all parameters already have clear descriptions in the schema. The tool description adds a brief summary ('the input parameters for Bazi chart calculation') but does not provide additional semantic meaning beyond what the schema offers. 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 purpose: perform Bazi chart calculation based on birth date/time and gender, returning detailed information and analysis. The verb '进行八字排盘' (perform Bazi chart calculation) is specific, and the resource '八字盘面' (Bazi chart) is well-defined. It distinguishes from the sibling tool 'divination_liu_yao', which is a different divination 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 description does not provide any guidance on when to use this tool versus alternatives. It does not mention prerequisites, when not to use it, or specific contexts. The sibling tool is noted but not compared. An agent would have no explicit guidance on choosing between Bazi and Liu Yao divination.

    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 must bear the full burden of disclosure. It only states 'returns detailed information' without describing side effects (e.g., automatic coin toss if yaogua omitted). Behavioral traits are insufficiently communicated.

    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 that is efficiently front-loaded with the tool's purpose. No 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 complexity of divination and the presence of an output schema, the description is minimally adequate. It lacks details on method (e.g., Chinese calendar or random generation) but covers basic inputs and output. Could improve by clarifying automatic coin toss behavior.

    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%, and the parameter descriptions in the schema are detailed (e.g., valid ranges, yaogua behavior). The main description adds no extra meaning beyond what the schema provides, so 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?

    The description clearly states the tool performs Six Yao divination layout based on year, month, day, and hour, and returns detailed information. It distinguishes from the sibling tool 'divination_bazi' by method, though not explicitly stated, making it clear enough.

    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 versus alternatives. The description does not mention any prerequisites or context for use, leaving the agent without direction on selecting between tools.

    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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