OpenAI Docs
Independent PiSkill directory guide. The original skill remains hosted by OpenAI Skills.
What is OpenAI Docs?
Helps Codex answer OpenAI product and API questions from current official documentation, with a retrieval-first workflow and source-grounded guidance.
What does OpenAI Docs do?
OpenAI Docs is an OpenAI skill for answering product and API questions from current official documentation instead of relying on stale model memory. It uses a retrieval-first workflow so guidance about APIs, SDKs, tools and platform behavior is tied to the relevant OpenAI documentation.
Who is OpenAI Docs best for?
- Developers integrating OpenAI APIs
- Teams checking current SDK or platform behavior
- Codex users asking implementation questions about OpenAI products
- Projects that need source-grounded OpenAI guidance
Common use cases
- Look up the current API pattern for a feature
- Confirm SDK parameters or platform behavior
- Answer OpenAI product questions with official sources
- Avoid implementing from outdated examples
How does OpenAI Docs work?
The skill retrieves the relevant OpenAI documentation before answering, then bases implementation guidance on those sources. It is designed to prefer official, current documentation and preserve source grounding when platform details may have changed.
Key benefits
- Reduces reliance on stale API memory
- Keeps answers grounded in official documentation
- Useful for fast-changing SDK and platform questions
- Supports implementation as well as product research
Things to know
- It only helps when the required documentation is available
- Documentation can still change after a response is generated
- Project-specific architecture decisions remain the developer's responsibility
Compatible tools
Frequently asked questions
What is the OpenAI Docs skill for?
Why is retrieval important for OpenAI API questions?
Related skills
Notion Research Documentation
Researches across available Notion material and produces a source-linked brief or documentation page that separates evidence, synthesis, gaps, and next actions.
Hugging Face Best Model Finder
Helps identify and compare strong Hugging Face models for a task using available benchmark information instead of choosing a model only by name or popularity.
Acquire Codebase Knowledge
Maps an existing repository into evidence-based codebase documentation covering stack, structure, architecture, conventions, integrations, testing, and technical concerns.
Customer Research
Researches a customer question across available internal and external sources, cross-checks findings, attributes sources, states confidence, and captures reusable knowledge for future support or account work.
Knowledge Synthesis
Combines information from knowledge bases, documents, messages, and other sources while weighting source authority, resolving conflicts, and expressing confidence in the resulting answer.
ChatGPT Apps
Builds ChatGPT Apps with an MCP server and interactive UI, covering tool design, app resources, metadata, testing, and integration with the Apps SDK.