Skip to main content
Glama

generate_documentation

Create Markdown or HTML API documentation from an OpenAPI session, including endpoints, schemas, examples, and security details; returns the saved file path.

Instructions

Generate comprehensive markdown documentation for the API and return the file path

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formatNoOutput format: 'markdown' for .md file or 'html' for interactive HTML documentation (default: markdown)
filenameNoFilename for the documentation (default: auto-generated from API title)
sessionIdYesThe session ID
groupByTagsNoGroup endpoints by tags (default: true)
includeExamplesNoInclude examples in documentation (default: false)
includeSecurityNoInclude security information in endpoints (default: true)
outputDirectoryNoDirectory to save the documentation file (default: current working directory)
includeEndpointsNoInclude endpoints documentation (default: true)
includeComponentsNoInclude components/schemas documentation (default: true)
includeTableOfContentsNoInclude table of contents (default: true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.1

TDQS

B3.2/5.0
Behavior3/5

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

No annotations exist, so the description carries the full burden. It usefully discloses that the tool writes a file and returns a file path, but says nothing about whether it requires an initialized session, whether it overwrites existing files, or how output location conflicts are handled.

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?

A single efficient sentence with the action front-loaded and no filler. It is arguably under-specified rather than bloated, which is not a conciseness failure, though 'comprehensive' is a soft modifier.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a ten-parameter file-writing tool with no annotations and no output schema, the description covers the outcome and return value but omits session prerequisites, side effects on disk, and the HTML option. The rich schema compensates for parameter detail but not for behavioral context.

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%, so all ten parameters including defaults are documented in the schema itself, making 3 the baseline. The description adds nothing about parameters and even narrows the output to markdown, which is slightly at odds with the enum.

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?

States a specific verb (Generate), resource (markdown documentation for the API), and even the return value (file path). It is distinguishable from read-only siblings like list_endpoints or get_components. Minor blemish: it says 'markdown' while the schema offers markdown and html output.

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 indication of when to use this versus the other session tools, no prerequisite that a session must exist first, and no guidance on when html output is preferable. The agent is left to infer the workflow entirely.

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