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LiL-Loco

Documentation MCP Server

by LiL-Loco

docs_generate_api

Generate API documentation directly from source code comments (JSDoc, docstrings) for TypeScript, Python, Go, and more. Specify project path, output path, and language to produce structured docs.

Instructions

Generate API documentation from code (JSDoc, Docstrings, etc.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageYesProgramming language
outputPathYesOutput path for API documentation
projectPathYesPath to the project source code
Behavior2/5

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

No annotations are provided, and the description does not clarify behavioral traits like whether the tool modifies project files, requires specific permissions, or produces a specific output format. The mention of 'from code' implies a read-only analysis but the outputPath parameter suggests writing, which is not explained.

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 a single concise sentence that front-loads the core purpose. It avoids unnecessary words, but could include a bit more detail without harming conciseness.

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?

With three required parameters, no output schema, and no annotations, the description is insufficiently complete. It does not explain what format the documentation is generated in (e.g., HTML, Markdown), where it is written, or how to interpret the output. The agent would lack enough information to use the tool correctly without external knowledge.

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?

The input schema has 100% description coverage for all three required parameters, each with a clear purpose. The description adds no additional meaning beyond what the schema already provides, achieving the baseline score.

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 generates API documentation from code comments like JSDoc or Docstrings, using a specific verb 'generate' and resource 'API documentation'. However, it does not differentiate from the sibling tool docs_generate_openapi, which also generates API documentation but specifically for OpenAPI.

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?

The description provides no guidance on when to use this tool versus alternatives such as docs_generate_openapi or docs_analyze_project. It lacks context about prerequisites, when not to use, or typical use cases.

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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