api-docs-generator
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Audits and enhances API documentation for FastAPI and REST endpoints. Identifies missing descriptions, incomplete response codes, missing examples, and generates enhanced docstrings, Pydantic model examples, and OpenAPI spec improvements. Triggers on: "generate API docs", "document this API", "OpenAPI for", "add examples to", "improve docstrings", "API documentation audit", "FastAPI docs", "document endpoints", "API reference", "swagger docs", "REST API docs", "endpoint documentation", "response documentation". Use this skill when API endpoints need documentation or documentation audit.
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NPX Install
npx skill4agent add mathews-tom/praxis-skills api-docs-generatorTags
Translated version includes tags in frontmatterSKILL.md Content
View Translation Comparison →API Docs Generator
Audits API endpoint documentation for completeness, generates enhanced docstrings with
proper parameter descriptions and examples, documents all response codes, and produces
Pydantic model examples — bridging the gap between auto-generated OpenAPI specs and
genuinely useful API documentation.
Reference Files
| File | Contents | Load When |
|---|---|---|
| FastAPI-specific documentation patterns, Path/Query/Body parameter docs | FastAPI endpoint |
| Creating realistic field examples, model_config patterns | Example values needed |
| Standard HTTP response documentation, error response schemas | Response documentation needed |
| OpenAPI spec enrichment, tag organization, schema documentation | OpenAPI spec review |
Prerequisites
- Access to the API source code (route definitions, models)
- Framework identification (FastAPI, Flask, Django REST, Express)
Workflow
Phase 1: Analyze Endpoints
- Inventory endpoints — List all routes with HTTP method, path, handler function.
- Identify models — Request bodies (Pydantic models, dataclasses), response models, query parameters, path parameters.
- Map dependencies — Authentication requirements, middleware, shared dependencies.
- Read existing docs — Current docstrings, OpenAPI metadata, inline documentation.
Phase 2: Audit Documentation
For each endpoint, check:
| Check | What to Verify | Common Gap |
|---|---|---|
| Endpoint description | Handler has a docstring | Missing or "TODO" |
| Parameter descriptions | Each param has | Path params undocumented |
| Request example | Body model has | No request example |
| Response model | | Returns raw dict |
| Error responses | 4xx/5xx documented with | Only 200 documented |
| Tags | Endpoint assigned to a tag group | Untagged endpoints |
Phase 3: Generate Enhancements
- Docstrings — Write clear endpoint descriptions that explain purpose, not implementation. Include Raises section for documented errors.
- Parameter metadata — Add ,
description,example/ge/leto Path, Query, Body parameters.regex - Model examples — Add and
Field(example=...)withmodel_config.json_schema_extra - Error responses — Document every possible error status code with response schema.
- Tags — Group endpoints by resource or feature area.
Phase 4: Output
Produce a coverage report and enhanced code.
Output Format
## API Documentation Audit
### Coverage Summary
| Metric | Count | Documented | Coverage |
|--------|-------|------------|----------|
| Endpoints | {N} | {M} | {%} |
| Parameters | {N} | {M} | {%} |
| Response codes | {N} | {M} | {%} |
| Models with examples | {N} | {M} | {%} |
### Gaps Identified
| # | Endpoint | Issue | Severity |
|---|----------|-------|----------|
| 1 | `{METHOD} {path}` | {issue} | {High/Medium/Low} |
### Enhanced Code
#### `{METHOD} {path}`
```python
@router.{method}(
"{path}",
response_model={ResponseModel},
summary="{Short summary}",
responses={{
404: {{"description": "{Not found description}"}},
422: {{"description": "Validation error"}},
}},
tags=["{tag}"],
)
async def {handler}(
{param}: {type} = Path(..., description="{description}", example={example}),
) -> {ResponseModel}:
"""
{Full description of what this endpoint does.}
{Additional context about behavior, side effects, or important notes.}
Raises:
404: {Entity} not found
403: Insufficient permissions
"""Model: {ModelName}
{ModelName}python
class {ModelName}(BaseModel):
{field}: {type} = Field(..., description="{description}", example={example})
model_config = ConfigDict(
json_schema_extra={{
"example": {{
"{field}": {example_value},
}}
}}
)text
## Calibration Rules
1. **Describe behavior, not implementation.** "Retrieves the user's profile" is good.
"Calls `db.query(User).filter_by(id=id).first()`" is implementation leakage.
2. **Realistic examples.** `"alice@example.com"` not `"string"`. `42` not `0`.
Examples serve as documentation — they should look like real data.
3. **Document every error code.** If the endpoint can return 404, document it. Users
should never encounter an undocumented error response.
4. **Consistent style.** All endpoints in the same API should use the same documentation
patterns — same tag naming, same description style, same example format.
5. **Don't duplicate the type system.** If the parameter type is `int`, don't write
"An integer" as the description. Write what the integer represents: "Unique user
identifier."
## Error Handling
| Problem | Resolution |
|---------|------------|
| Non-FastAPI framework | Adapt patterns. Document the HTTP contract regardless of framework. |
| No type hints on handlers | Infer types from usage, document uncertainty, suggest adding type hints. |
| Massive API (50+ endpoints) | Prioritize undocumented and public endpoints. Batch output by resource. |
| Generated API (OpenAPI → code) | Document at the spec level, not the generated code level. |
| Authentication varies by endpoint | Document auth requirements per endpoint group. |
## When NOT to Generate
Push back if:
- The API design itself is wrong (bad URL patterns, wrong HTTP methods) — fix the API first
- The user wants SDK generation from OpenAPI — different tool
- The code is a prototype that will change significantly — document after stabilization