mcp-pandoc
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
There is only one tool, so there is no possibility of an agent mistaking it for another. Its purpose is clearly defined as content conversion, with no overlapping tools.
Naming Consistency5/5Although there is only one tool, the name 'convert-contents' follows a clear verb_noun convention and is semantically appropriate. With no other tools, there are no naming conflicts or mixed conventions.
Tool Count3/5A single tool for Pandoc conversion feels minimal, though it can cover many conversions through its parameters. It is on the thin side of the acceptable range for a focused converter server.
Completeness5/5The tool supports conversion across a wide range of formats, including inline returns and file outputs, plus advanced options like reference documents, filters, and defaults files. For a conversion-only server, this covers the domain thoroughly with no obvious operational gaps.
Average 4.3/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 4 community issues answered or closed in the last 6 months
- 18 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.
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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 provided, the description carries the full burden of behavioral disclosure. It does well by explaining that PDF conversion requires TeX Live, that filenames won't be auto-generated, that files may be saved to temp directory if no path is given, and that pptx is write-only. It also mentions the success message that reveals the saved location. The only minor gap is not explicitly stating whether operations are reversible or if any destructive actions occur, but for a conversion tool, this is less critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is excessively long and repetitive. Key information about file paths is repeated multiple times (e.g., in the critical requirements, incorrect usage examples, and the final note). The use of emojis, many sections, and multiple examples makes it hard to scan quickly. While it is front-loaded with the main purpose, the sheer volume undermines conciseness.
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 highly complete given the tool's complexity. It covers all major usage scenarios, including basic conversions, advanced format path requirements, styling with reference documents, Pandoc filters, and defaults files. It even explains output location and success messages, which is valuable since there is no output schema. The description leaves little room for user confusion about how to proceed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema already provides descriptions for all 8 parameters, the tool description significantly enriches parameter understanding. It explains the purpose and usage of `reference_doc`, `filters`, `defaults_file`, and clarifies the importance of `output_file` for advanced formats. For example, it gives a specific example for using filters with Mermaid diagrams and explains that reference documents must match output format. This adds substantial value beyond the schema.
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 first sentence clearly states the tool's function: 'Converts content between different formats.' This is a specific verb+resource description that distinguishes it from potential alternative tools. The rest of the description reinforces this with supported formats and examples. However, the purpose is somewhat diluted by the extensive additional requirements and feature explanations.
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?
The description provides explicit, actionable guidance on when and how to use the tool, including correct and incorrect usage examples, requirements for PDF conversion, and file path specifications. It clearly delineates basic vs. advanced formats and instructs users to always specify content, output format, and complete file paths for advanced formats. This goes beyond mere context to offer concrete usage rules.
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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