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jpbullalayao

Pokémon VGC Damage Calculator MCP Server

by jpbullalayao

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined and distinct by default.

    Naming Consistency5/5

    A single tool inherently has consistent naming, as there are no other tools to compare it against. The name 'calculateDamage' follows a clear verb_noun pattern.

    Tool Count2/5

    One tool is too few for a server named 'Pokémon VGC Damage Calculator MCP Server', which implies a domain requiring multiple operations like damage calculation, stat lookup, move effects, or team analysis. A single tool feels incomplete for the apparent scope.

    Completeness2/5

    The server is severely incomplete for its domain. While damage calculation is a core function, there are obvious gaps such as missing tools for retrieving Pokémon stats, moves, abilities, or handling team compositions, which are essential for a comprehensive VGC calculator.

  • Average 2.8/5 across 1 of 1 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 status not available
  • 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?

    With no annotations provided, the description carries full burden for behavioral disclosure. It mentions what factors are considered but doesn't explain computational complexity, accuracy limitations, whether it's deterministic, or what the output format looks like. This leaves significant gaps for a complex calculation tool.

    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, well-structured sentence that efficiently communicates the core functionality without unnecessary words. It's appropriately sized for a tool with this complexity level.

    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?

    For a complex calculation tool with 4 nested parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain the calculation methodology, output format, error conditions, or provide examples of proper usage.

    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?

    With 0% schema description coverage and 4 complex parameters (attacker, defender, move, field), the description only vaguely mentions 'stats, abilities, items, and field conditions' without explaining parameter relationships, required data formats, or how these inputs map to the damage calculation. It fails to compensate for the complete lack of schema documentation.

    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's purpose with a specific verb ('calculates') and resource ('battle damage'), and lists key factors considered (stats, abilities, items, field conditions). However, without sibling tools to differentiate from, it cannot achieve a perfect 5.

    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 is provided on when to use this tool versus alternatives, prerequisites, or specific battle scenarios where it's applicable. The description only states what it does, not when it should be invoked.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • 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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