openai-docs
by openaiUse openai-docs for Technical Writing, OpenAI API and product questions, model selection, migration checks, and prompt-upgrade guidance. It prioritizes official OpenAI docs via the Developer Docs MCP server, with bundled references as fallback context only when needed.
This skill scores 86/100, which means it is a solid directory listing for users who need official OpenAI documentation help, model selection, and migration guidance. The repository gives enough trigger language, workflow steps, and supporting references for agents to use it with far less guesswork than a generic prompt, though some operations still depend on external MCP availability and remote freshness checks.
- Explicit trigger covers OpenAI docs lookup, latest-model selection, model migration, and prompt-upgrade work.
- Clear operational flow: prioritize the OpenAI Docs MCP tools, then use bundled references and a freshness-check script when needed.
- Good install decision value: valid frontmatter, no placeholder markers, and multiple references/scripts supporting real workflows.
- Core functionality depends on the developers.openai.com MCP server being installed and responsive; fallback paths are secondary.
- Bundled model guidance is explicitly labeled as helper/fallback context and may need freshness verification before reuse.
Overview of openai-docs skill
What openai-docs is for
The openai-docs skill helps you answer OpenAI API and product questions with current, official documentation instead of stale memory or generic prompting. It is especially useful when you need source-backed guidance on model choice, API behavior, migration steps, or prompt changes that affect production quality.
Who should use it
Use the openai-docs skill if you are doing Technical Writing for OpenAI integrations, maintaining an app that depends on OpenAI models, or validating a recommendation before you ship it. It is a strong fit when the main risk is being outdated, not creative.
What makes it different
The skill is built around the OpenAI Developer Docs MCP server, so the default workflow is doc search, exact section fetch, and only then fallback browsing on official OpenAI domains if needed. That makes openai-docs more reliable than a freeform prompt when you need citations, current model names, or migration-safe advice.
How to Use openai-docs skill
Install and activate openai-docs
Install with npx skills add openai/skills --skill openai-docs. The key setup requirement is access to the openaiDeveloperDocs MCP server at https://developers.openai.com/mcp; without it, the skill may fall back, but the best experience depends on the docs server being available.
Start from the right files
Read SKILL.md first, then check references/latest-model.md, references/prompting-guide.md, and references/upgrade-guide.md for the parts of the workflow that affect model selection and upgrades. If you are validating the integration itself, agents/openai.yaml shows the intended tool dependency and default task framing, while scripts/resolve-latest-model-info.js explains how freshness checks are resolved.
Give the skill a usable prompt
The best openai-docs usage is not “tell me about GPT-5.5,” but a task-shaped request like: “Use openai-docs to compare the latest OpenAI model for a customer-support assistant, note any prompt changes needed, and cite the specific docs sections.” Include your use case, current model, whether you need a migration or a new integration, and any constraints like latency, cost, or tool use.
Follow the workflow that improves output
For lookup tasks, ask for the specific doc page or section you need. For model-selection tasks, explicitly say whether the target is latest, current, default, or pinned; the skill preserves explicit targets and only resolves the latest model when the target is ambiguous. For migration tasks, mention the old model, the desired outcome, and whether you want a narrow upgrade or a broader prompt rewrite.
openai-docs skill FAQ
Is openai-docs only for API docs?
No. The openai-docs skill also covers model selection, API model migration, and prompt-upgrade guidance. That makes it useful when the question is not just “how does this endpoint work?” but “what should I change in my implementation and prompts?”
How is this different from a normal prompt?
A normal prompt can summarize from memory, but openai-docs is designed to look up current official sources first and stay anchored to the docs. That matters when the answer depends on recent model changes, exact parameter names, or compatibility details that are easy to get wrong from recall.
Is openai-docs good for beginners?
Yes, if the user has a concrete OpenAI task. It is less helpful for open-ended learning with no specific goal, and it is not the best choice if you want a general explanation disconnected from current OpenAI docs.
When should I not use it?
Do not use openai-docs when the question is unrelated to OpenAI products, when you need broad web research beyond official OpenAI sources, or when you already have a pinned implementation that should not be updated. It is also a poor fit for speculative architecture advice that does not need documentation grounding.
How to Improve openai-docs skill
Improve the input before you ask for output
Stronger inputs produce better openai-docs usage. Give the model your current model ID, target behavior, product surface, and the exact artifact you want back: a comparison table, migration checklist, rewritten prompt, or cited summary. For openai-docs for Technical Writing, also say whether the output should read like implementation notes, release notes, or a doc draft.
Be explicit about what must stay unchanged
The skill is most useful when you tell it what is pinned: model version, endpoint, tool stack, latency budget, or backward compatibility constraints. That prevents unnecessary upgrades and keeps the answer focused on the smallest safe change.
Watch for the common failure modes
The main failure mode is asking for “the latest” without a use case; that can produce a generic recommendation instead of a decision. Another is asking for a migration without naming the current model or whether prompt changes are allowed. If the first answer is too broad, narrow it by asking for only the relevant docs sections and the one action you want to take next.
Iterate with verification
Use the first pass to locate the right docs and the second pass to turn them into an implementation decision. If you are updating documentation, ask the skill to separate confirmed facts from assumptions and to flag any places where a pinned model or legacy example should remain unchanged.