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perryjr1444-ux

Autonomous Documentation MCP

generate_api_reference

Create API reference documentation from code annotations, JSDoc, docstrings, and type definitions to maintain synchronized documentation across programming languages.

Instructions

Generate API reference documentation from code annotations, JSDoc, docstrings, and type definitions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
source_pathYesPath to source code for API extraction
output_pathNoOutput path for API reference
formatNoOutput formatmintlify
include_privateNoInclude private/internal APIs
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool's function but lacks details on critical behaviors such as error handling, processing time, file system impacts, or output characteristics. For a tool that generates documentation, this is a significant gap in transparency.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the key action and resources, making it easy to parse quickly, which is ideal for 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?

Given the complexity of generating API documentation and the lack of annotations and output schema, the description is incomplete. It doesn't address behavioral aspects like what happens if source_path is invalid, how output is structured, or any dependencies, leaving gaps that could hinder effective tool use by an agent.

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 description coverage is 100%, meaning the input schema fully documents all four parameters. The description adds no additional parameter semantics beyond what's in the schema, such as examples or constraints. However, since the schema is comprehensive, a baseline score of 3 is appropriate as the description doesn't need to compensate.

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 action ('Generate API reference documentation') and source materials ('from code annotations, JSDoc, docstrings, and type definitions'), which is specific and informative. However, it doesn't explicitly differentiate this tool from sibling tools like 'generate_documentation' or 'create_docs_config', which might have overlapping functionality, preventing a perfect score.

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. With siblings like 'generate_documentation' and 'create_docs_config' present, there's no indication of specific use cases, prerequisites, or exclusions, leaving the agent to guess based on tool names alone.

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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