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quickquickTax

Korean Capital Gains Tax Advisor MCP Server

by quickquickTax
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TypeScript
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: listing supported scenarios, validating a case, and calculating tax. No overlap or ambiguity.

    Naming Consistency5/5

    All tools follow a consistent 'verb_noun' pattern in snake_case (calculate_capital_gains_tax, list_supported_capital_gains_scenarios, validate_capital_gains_case).

    Tool Count5/5

    Three tools cover the essential workflow of discovery, validation, and calculation, appropriate for a focused tax advisor server.

    Completeness5/5

    The tool set covers the full lifecycle: check what's supported, validate a case, then calculate. No obvious missing operations for the stated purpose.

  • Average 4.2/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 26 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

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  • 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

  • Behavior4/5

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

    Annotations declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, openWorldHint=false. The description adds behavioral context: it rejects unsupported cases, is deterministic, and provides estimates. 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.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is three sentences with purpose, constraints, and disclaimer. It is front-loaded and efficient. Minor bilingual mix (English/Korean) could be streamlined but does not hinder clarity.

    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?

    The description covers tool behavior and limitations but lacks output schema details. It mentions estimates for tax and local income tax but no info on return structure. Given nested input complexity, output specification would enhance completeness.

    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 100% with detailed types and descriptions. The description adds only that the input must be 'complete, validated case,' which is already implied by the schema's required fields and descriptions. No extra parameter-level detail beyond schema.

    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 'deterministically estimates Korean real-estate capital gains tax and local income tax from a complete, validated case,' specifying the verb (estimates), resource (tax), and scope. It distinguishes from siblings: list_supported_capital_gains_scenarios and validate_capital_gains_case are different functions.

    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 lists rejected cases (multiple transfers, inheritance/gift) and notes results are estimates, providing guidance on when not to use. It implies use for complete validated cases but lacks explicit comparison with siblings.

    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=true and idempotentHint=true, indicating safe behavior. The description adds value by specifying that the tool lists unsupported cases and cautions, beyond what annotations provide.

    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 concise sentences: first states what the tool does, second provides usage guidance. No unnecessary words, front-loaded with key 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?

    Given the simple parameter, rich annotations, and clear siblings, the description is sufficient. It describes the output types (supported scenarios, unsupported cases, cautions) without needing an output schema.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema description coverage is 0%, and the description does not mention the 'detailLevel' parameter or its enum values. The parameter is simple but description fails to add meaning.

    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 lists supported rule dates, scenarios, unsupported cases, and usage cautions. It is a distinct pre-check tool compared to siblings 'calculate_capital_gains_tax' and 'validate_capital_gains_case'.

    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 advises using this tool before collecting case details when support is uncertain, providing clear context for use. It does not explicitly state when not to use, but the guidance is strong.

    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 declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds specifics on what gets validated (required fields, dates, shares, rules, scenarios) and the instruction not to infer missing values, providing 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?

    Two sentences, zero wasted words. First sentence states purpose and scope, second sentence gives critical usage instruction.

    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?

    Description covers what it validates and usage order, but does not indicate what the output is (validation errors/success, or return structure). Given no output schema, this gap reduces completeness for a validation tool.

    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?

    Schema coverage is 100% but parameter description is minimal ('data to validate; partial fields okay'). Tool description adds value by detailing what aspects are validated, enhancing meaning for the single parameter.

    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 it validates required fields, dates, ownership shares, rule applicability, and supported scenarios before calculating Korean real-estate capital gains tax. It also distinguishes itself from sibling tools by specifying 'call this tool first'.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicitly says 'Call this tool first and do not infer missing values,' providing clear when-to-use and when-not-to-use guidance relative to calculate_capital_gains_tax.

    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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  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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