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maekawataiki

mcp-pandoc-md2pptx

by maekawataiki
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

67%
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. The tool's purpose is clearly defined and distinct.

    Naming Consistency5/5

    The single tool 'convert-contents' uses a clear and descriptive verb_noun pattern. Consistency is not an issue with only one tool.

    Tool Count4/5

    One tool is appropriate for a focused converter server. However, the tool must handle multiple aspects (templates, diagrams), which could justify additional tools for better separation.

    Completeness5/5

    The tool covers all necessary functionality for the Markdown-to-PPTX conversion use case: input format, template support, diagram rendering, and file output. No obvious gaps.

  • Average 4.4/5 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
    • Last stable release on
    • 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.

  • 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?

    With no annotations, the description must carry the burden. It discloses key behaviors: supports only Markdown input and PPTX output, requires complete file paths, supports diagram types (mermaid, plantuml, graphviz), and template usage. No contradictions. It could mention error handling or file size limits, but overall transparent.

    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 moderately long but well-structured using headings, bullet points, and examples. Every section adds value (requirements, examples, diagram support, template creation). The core purpose is front-loaded, and the format is scannable. Could be slightly more concise, but effective.

    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?

    Given the tool's complexity (4 params, no output schema, no siblings), the description covers all necessary aspects: input/output formats, file path requirements, template usage, diagram support, and even how to generate templates. It provides complete guidance for correct invocation.

    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?

    Input schema has 100% description coverage, so baseline is 3. The description adds significant value beyond schema: explains the oneOf relationship between contents and input_file, provides real usage examples for template, and details diagram support. This extra context justifies a score of 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 explicitly states 'Converts Markdown content to PowerPoint (PPTX) format.' It clearly identifies the input format (Markdown), output format (PPTX), and the tool's action, leaving no ambiguity. With no sibling tools, differentiation is irrelevant, but the description is exceptionally clear.

    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 explicit requirements: input must be Markdown, output only PPTX, complete file path required. It includes usage examples and mentions template and diagram support. While it lacks explicit 'when not to use' or alternative tools (none exist), the context is very clear and practical.

    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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