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openfate-ai

OpenFate Bazi MCP

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by openfate-ai

Server Quality Checklist

75%
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  • Latest release: v0.2.2

  • Disambiguation5/5

    Each tool targets a distinct operation: chart calculation, solar time correction, interaction detection, policy retrieval, resource listing, and reverse lookup. No overlapping functionality.

    Naming Consistency5/5

    All tools follow a consistent verb_noun pattern in snake_case (e.g., calculate_bazi_chart, detect_bazi_interactions), making the naming predictable and clear.

    Tool Count5/5

    With 6 tools, the server is well-scoped for a specialized Bazi domain. Each tool serves a distinct purpose without redundancy or unnecessary complexity.

    Completeness5/5

    The tool set covers the full lifecycle for Bazi chart calculations: time adjustment, chart generation, interaction analysis, reverse lookup, and supporting resources/policy. No obvious gaps.

  • Average 4/5 across 6 of 6 tools scored.

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

    • No community issues in the last 6 months
    • 24 commits in the last 12 weeks
    • Last stable release on
    • 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

  • Behavior3/5

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

    Annotations already declare readOnlyHint and idempotentHint true. The description adds context on what is returned (policy and guidance), which is useful beyond 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?

    Single sentence, no waste. Perfectly concise for a parameterless tool.

    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 no output schema and zero parameters, the description adequately states the return content. Could mention it is intended for LLM guidance before chart calculations.

    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?

    No parameters; schema coverage is 100%. Description adds no param info, which is fine as there are none.

    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 it returns policy and LLM guidance for Bazi chart calls. It distinguishes from siblings like get_openfate_bazi_resources, but doesn't explicitly differentiate.

    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 or alternatives. Given siblings, a note on when to use this vs get_openfate_bazi_resources would help.

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

  • Behavior4/5

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

    Annotations already indicate read-only, non-destructive, idempotent. The description adds that the calculation is deterministic and uses true solar time correction, providing extra context beyond annotations. No contradictions.

    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: first states purpose, second gives guidance. No wasted words, highly efficient.

    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?

    While the tool is complex with 14 parameters, the description covers purpose and key features. However, it does not describe the output format or list expected return fields, which is a gap given the absence of an 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?

    Schema description coverage is 100%, so the schema already documents parameters. The description adds a tip about accuracy but does not further explain parameter meanings or relationships, so it adds minimal value.

    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 calculates a Bazi/Four Pillars chart with specific features (true solar time, Day Master, Da Yun cycles, branch interactions). It does not explicitly distinguish from sibling tools, but the purpose is sufficiently clear.

    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 advises passing longitude and timezone/timezoneId for best accuracy, providing some guidance. However, it lacks explicit when-to-use vs alternatives or conditions under which this tool should be preferred over 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?

    Annotations already declare readOnlyHint, destructiveHint, and idempotentHint, so the description adds no new behavioral context beyond the intended use case. It does not contradict annotations, but does not enhance transparency.

    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, no wasted words, front-loaded with the core purpose. Every sentence earns its place.

    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?

    With 9 parameters and no output schema, the description fails to explain return values, units, or how the result should be interpreted. This is a significant gap for a complex calculation tool.

    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 44%, and the description only groups inputs generally without adding per-parameter meaning. The description does not compensate for the missing schema descriptions, leaving some parameters under-documented.

    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 calculates True Solar Time from specific inputs and distinguishes itself by mentioning the hour pillar difference from ordinary clock-time tools, which efficiently separates it from sibling tools.

    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 a specific use case ('when explaining why the hour pillar may differ') but does not explicitly state when not to use it or list alternatives, though the context of sibling tools implies differentiation.

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

  • Behavior4/5

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

    Annotations indicate readOnlyHint, destructiveHint false, idempotentHint true; description confirms deterministic nature, no contradictions.

    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, front-loaded with purpose and scope, 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 simplicity and full schema coverage, description adequately covers usage and return types (list of interaction types). No output schema needed.

    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 has 100% coverage with descriptions. Description adds minimal extra meaning (e.g., hourBranch can be omitted, annualBranch for dynamic detection), but baseline 3 applies.

    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?

    Description states specific verb 'detect' and resource 'Earthly Branch interactions', and lists categories (clashes, combinations, etc.). Distinguishes from siblings like calculate_bazi_chart.

    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?

    Explicitly mentions use cases: natal charts, synastry, annual triggers, target-branch comparison. Provides clear context but does not explicitly exclude alternatives.

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

  • Behavior4/5

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

    Annotations already indicate readOnly, destructive, idempotent, and open-world hints. The description adds specific behavioral context: the lookup uses 'clock-time pillars without location-based true solar correction,' which is critical for understanding result accuracy. No contradictions with 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 extremely concise: two sentences that front-load the purpose and add one essential behavioral note. Every sentence is necessary and 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 5 parameters, 100% schema coverage, and no output schema, the description provides the core use case and a key behavioral detail. It could mention the output format (list of datetimes) but is otherwise 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 does not add meaning beyond the schema for individual parameters, but it contextualizes the overall lookup behavior. No contradiction.

    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: 'Find possible Gregorian datetimes that produce a given four-pillar Bazi string.' It uses a specific verb ('find') and resource ('Gregorian datetimes'), differentiates from sibling tools by mentioning the lookup is without true solar correction, and is useful when a user only has a Bazi chart.

    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 implies when to use the tool (when a user has a Bazi string and wants possible datetimes) and notes the lack of solar correction, hinting that for solar-adjusted times another tool (calculate_true_solar_time) may be needed. However, it does not explicitly list when not to use it or name alternatives.

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

  • Behavior4/5

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

    Annotations declare readOnlyHint, idempotentHint, and non-destructive. The description adds the list of URL types returned, which is useful context beyond 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?

    A single sentence that is front-loaded with the verb 'Return' and the resource type. Every word adds value; no filler.

    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?

    For a tool with no parameters and a clear purpose of returning static URLs, the description enumerates all relevant URL categories, providing sufficient completeness without an output schema.

    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?

    No parameters exist; schema coverage is 100%. The description correctly omits parameter details, and the baseline for zero-parameter tools 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 returns canonical OpenFate URLs, listing specific resource types (charting, readings, compatibility, etc.). This distinguishes it from sibling computation tools like calculate_bazi_chart.

    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 implies the tool is for retrieving URLs rather than performing calculations, but it does not explicitly state when to use this versus sibling tools or provide exclusion criteria.

    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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  • Evaluate tool definition quality.

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