taiwan-holiday-mcp
Server Quality Checklist
Latest release: v1.0.5
- Disambiguation5/5
Each tool targets a distinct query type: a single date check, a date range listing, and aggregated statistics. There is no overlap in purpose, making selection unambiguous.
Naming Consistency5/5All tool names follow a clear verb_noun pattern: check_holiday, get_holidays_in_range, get_holiday_stats. The minor singular/plural variation is semantically appropriate and does not break consistency.
Tool Count5/5With only 3 tools, the server is tightly scoped to its niche purpose (Taiwan holiday lookup). Each tool covers a distinct and necessary function without bloat.
Completeness5/5The tool set fully covers the core holiday querying lifecycle: single-date lookup, range listing, and statistical summaries. Since holidays are fixed data, no update/delete operations are needed, so there are no gaps.
Average 3.3/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 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, and the description does not disclose behavioral details such as return format, handling of invalid dates, or what constitutes a 'holiday' (e.g., official calendar). The description carries the full burden and is minimal.
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 a single, concise sentence in Chinese that is front-loaded and free of fluff. Every word contributes to the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema or annotations, the description should explain what the tool returns (e.g., true/false) and any relevant context about holiday definitions. It does neither, making it incomplete for an agent to fully understand the tool's behavior.
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?
The input schema covers the single parameter (date) with format constraints and description. The tool description adds no additional parameter semantics beyond the schema, so the baseline of 3 applies.
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 checks if a specified date is a Taiwan holiday. It uses a specific verb ('check') and resource ('date is Taiwan holiday'), distinguishing it from sibling tools that handle ranges or statistics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus the alternatives (get_holidays_in_range, get_holiday_stats). The intended use case (single-date checking) is implied by the name and description but not explicitly contrasted with siblings.
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 carries full responsibility. It only states the function without disclosing behavioral traits like return format, aggregation details, or potential limitations (e.g., date boundaries). This is a significant gap.
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 a single, clear sentence that front-loads the verb and resource, with no unnecessary words. It is appropriately concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description omits what 'statistics' means or what the response contains. For a tool with two parameters, this is under-specified and leaves the agent guessing about the return value.
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?
The input schema covers 100% of parameters, with year and month each having descriptions. The description adds minimal semantic value, only reaffirming that the tool works for a year or year-month combination, which is already implied by the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves Taiwan holiday statistics for a specified year or year-month, using a specific verb (獲取) and resource (台灣假期統計資訊). However, it does not explicitly differentiate from sibling tools like check_holiday or get_holidays_in_range, though the 'statistics' focus implies a different use case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly conveys usage: use when you need Taiwan holiday statistics for a year or month. It lacks explicit guidance on when to prefer this tool over siblings, such as when checking a single date or a range.
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 carries the full burden of disclosing behavior. However, it only states the purpose (retrieving holidays in a range) and does not mention return format, error handling, rate limits, or whether it is a read-only operation. This leaves significant behavioral context unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the core action and resource. It contains no wasted words and is appropriately minimal for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two parameters, and the schema adequately documents those. However, there is no output schema, and the description does not clarify the return structure or format (e.g., a list of holiday objects). The description implies the result is all holidays in the range, but a bit more detail would make it more complete.
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?
The schema covers 100% of parameters with descriptions of date formats (YYYY-MM-DD or YYYYMMDD). The description adds no additional parameter semantics beyond what the schema already provides, so the baseline score of 3 applies.
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 '獲取' (get) with a clear resource '所有台灣假期' (all Taiwan holidays) and scope '指定日期範圍內' (within specified date range). This clearly differentiates it from sibling tools like check_holiday (which checks a single date) and get_holiday_stats (which provides statistics).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for retrieving holidays within a date range, but it does not explicitly state when to use this tool versus alternatives like check_holiday or get_holiday_stats. No exclusions or alternative guidance is provided.
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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