asktian MCP Server
Server Quality Checklist
Latest release: v0.2.0
- Disambiguation5/5
Each tool targets a distinct aspect of Chinese metaphysics: scheduling, compatibility, personal daily reading, name analysis, and general day energy. There is no overlap in functionality.
Naming Consistency5/5All tool names follow a consistent 'asktian_' prefix with descriptive snake_case names, e.g., 'asktian_best_time_for_action'. Pattern is uniform.
Tool Count5/5With 5 tools, the server is well-scoped for a niche domain like Chinese metaphysics. Each tool serves a specific purpose without redundancy.
Completeness4/5Covers common queries like daily guidance, compatibility, name analysis, and timing. Minor gap: no explicit birth chart rendering tool, but daily_reading provides archetype and energy.
Average 4.3/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 22 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.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
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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
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It discloses the return format (top 3 windows + windows to avoid) and real-time decision support context, but does not explicitly state it is read-only or non-destructive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with the core purpose and includes concise usage examples. The final sentence is somewhat self-promotional but still adds context about the tool's value; minor trimming could improve.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple query tool, the description covers purpose, usage triggers, and return format. No output schema exists, but the description explains what is returned. It is adequate given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline 3 is justified. The description does not add extra parameter details beyond what is already in the schema, but the enum action parameter gets helpful guidance ('pick closest match').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds 'most auspicious time windows' for a specific action, distinguishing it from siblings like asktian_compatibility or asktian_today_energy which handle different tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit examples of when to use ('when should I do X', etc.) and implies use over sibling tools by focusing on scheduling advice, but lacks explicit 'when not to use' instructions.
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?
No annotations provided, so description carries full burden. Discloses return values and methodology (bazi + daily energy). Does not mention side effects (none expected) or permissions, but is sufficient for a read-like tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single efficient paragraph, front-loaded with purpose. Slightly repetitive but no superfluous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity and no output schema, description adequately covers what the tool does, returns, and when to use. Missing exact return format but understandable from listing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%. Description adds no extra parameter meaning beyond what schema already provides (e.g., defaults, enum options). Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it provides a personalized daily reading based on Chinese metaphysics, listing specific outputs (archetype, energy, colors, etc.). Differentiates from siblings like asktian_today_energy by emphasizing personalization via birthdate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly gives use cases: 'when the user asks how today will be for them, what colors to wear, where to face their desk, or for general daily guidance.' No exclusion criteria but clear context.
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, the description fully carries the burden and explicitly discloses the hidden score behavior (<60) and the design principle behind it, which is valuable for agent decision-making.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, starts with the core purpose, and every sentence adds value without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 3 parameters, no output schema, the description covers input and output behavior adequately. It could mention that the tool relies on Chinese metaphysics, but that is implied by the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does 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 description adds no additional parameter meaning beyond the schema, but the schema already describes the two required birthdate parameters and the optional dimension with enum.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb (compute) and resource (fate compatibility via Chinese metaphysics) and clearly distinguishes it from sibling tools like asktian_best_time_for_action or asktian_daily_reading.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states 'Useful when user asks about compatibility, fit, or will this person and I work', providing clear use cases. It does not explicitly mention when not to use or list alternatives, but the context makes it sufficient.
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?
With no annotations, the description carries full burden. It discloses the output ('one-line vibe + dominant element guess') and implies it's quick and non-destructive. No contradictions or surprises. Could be slightly more explicit about the underlying mechanism or limitations, but sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no wasted words. Efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, no output schema), the description covers input, usage, and output. It could optionally detail the output format (e.g., 'vibe: ______, element: ______') but is complete enough for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds context about what types of names are suitable (person, baby, company) but does not add technical details beyond the schema. Language parameter's enum is clear from schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool does a 'Quick energetic profile of a name' and lists specific use cases (baby name, company name, 'what kind of person is X'). It distinguishes from sibling tools like asktian_best_time_for_action or asktian_compatibility which focus on timing and compatibility.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: 'when the user asks about someone's name, a baby name, a company name, or 'what kind of person is X' when no birthdate is available.' This provides clear guidance on when to choose this tool over 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?
No annotations, but description fully discloses what the tool returns (stem+branch, dominant 5-element). It does not mention side effects or auth needs, but for a read-only computation tool this is acceptable. The description is transparent about behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words, front-loaded with purpose. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is complete for a simple tool with one optional parameter and no output schema. It covers purpose, usage, and output clearly. No missing information needed for an AI agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter, and the description adds context ('Optional ISO YYYY-MM-DD. Defaults to today (UTC)'). The description does not further enhance parameter semantics 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get today's GENERAL energy' and specifies the outputs (干支 + dominant 5-element). It distinguishes from siblings by emphasizing 'no person needed' and that it's for generic context without birthdate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly describes when to use: when user asks about 'what kind of day' or for generic cosmic context without user's birthdate. Implies when not to use (when personalized info is available), with sibling tools provided for alternatives.
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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