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 | | ----------------------------------- | ----------------------------------------------------------------------- | ----------------------------- | | references/fastapi-patterns.md | FastAPI-specific documentation patterns, Path/Query/Body parameter docs | FastAPI endpoint | | references/example-generation.md | Creating realistic field examples, model_config patterns | Example values needed | | references/response-codes.md | Standard HTTP response documentation, error response schemas | Response documentation needed | | references/openapi-enhancement.md | 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

1. Inventory endpoints — List all routes with HTTP method, path, handler function.
2. Identify models — Request bodies (Pydantic models, dataclasses), response models, query parameters, path parameters.
3. Map dependencies — Authentication requirements, middleware, shared dependencies.
4. 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 description= | Path params undocumented | | Request example | Body model has example= or json_schema_extra | No request example | | Response model | response_model= specified | Returns raw dict | | Error responses | 4xx/5xx documented with responses= | Only 200 documented | | Tags | Endpoint assigned to a tag group | Untagged endpoints |

Phase 3: Generate Enhancements

1. Docstrings — Write clear endpoint descriptions that explain purpose, not implementation. Include Raises section for documented errors.
2. Parameter metadata — Add description, example, ge/le/regex to Path, Query, Body parameters.
3. Model examples — Add Field(example=...) and model_config with json_schema_extra.
4. Error responses — Document every possible error status code with response schema.
5. 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}

class {ModelName}(BaseModel):
    {field}: {type} = Field(..., description="{description}", example={example})

    model_config = ConfigDict(
        json_schema_extra={{
            "example": {{
                "{field}": {example_value},
            }}
        }}
    )

## 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