When writing or updating API skill docs, treat documentation as an operational dependency: prefer the most up-to-date source, keep docs self-contained, and make examples unambiguous. Apply these rules: 1) **Prefer live indexed documentation (MCP) when available** - If an indexed doc tool like `search_documentation` exists, use it as the only doc source. - Don’t fetch URLs manually when MCP tools are present. - After getting the needed syntax/fields, **generate the code immediately** (avoid long re-check cycles). 2) **Make docs portable and discoverable** - Avoid relative links that break in isolated contexts (e.g., `../...`). Use stable full paths or inline the required guidance. - Ensure new skills are listed/linked from the project’s main docs, and structure docs to avoid duplication. 3) **Define key terms explicitly** - If the API distinguishes concepts (e.g., **model** vs **agent**), define what each means and when to set each. 4) **Specify example placeholder types and formats** - For any placeholder like `frame`, document the expected type/encoding (e.g., bytes, base64 string, MIME type, tensor) so developers can pass correct inputs. Example (self-contained documentation snippet): ```python # `frame` must be raw bytes for a single image frame, encoded as JPEG/PNG bytes # (or provide the required mime_type for the SDK wrapper). # If you pass base64 strings, convert them to bytes (or use the SDK's expected field type). await session.send_realtime_input( video=types.Blob(data=frame_bytes, mime_type="image/jpeg") ) ``` Use this checklist during review to prevent stale guidance, broken links, and “works in theory” examples that fail at integration time.