Use the OpenAI Developer Documentation MCP server to search and fetch exact docs (markdown), then base your answer on that text instead of guessing.
Works with
Use the OpenAI Developer Documentation MCP server to search and fetch exact docs (markdown), then base your answer on that text instead of guessing.
If the mcp__openaiDeveloperDocs__* tools are available, use them.
If you are unsure, run codex mcp list and check for openaiDeveloperDocs.
mcp__openaiDeveloperDocs__search_openai_docs → pick the best URL.mcp__openaiDeveloperDocs__fetch_openai_doc → retrieve the exact markdown (optionally with an anchor).mcp__openaiDeveloperDocs__get_openapi_specmcp__openaiDeveloperDocs__list_api_endpointsBase your answer on the fetched text and quote or paraphrase it precisely. Do not invent flags, field names, defaults, or limits.
Provide one of these setup options, then ask the user to restart the Codex session so the tools load:
codex mcp add openaiDeveloperDocs --url https://developers.openai.com/mcp~/.codex/config.toml):
[mcp_servers.openaiDeveloperDocs]
url = "https://developers.openai.com/mcp"
Also point to: https://developers.openai.com/resources/docs-mcp#quickstart
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionopenai-knowledgeExecute the skills CLI command in your project's root directory to begin installation:
Fetches openai-knowledge from openai/openai-agents-python and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate openai-knowledge. Access via /openai-knowledge in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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openai-knowledge reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in openai-knowledge — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: openai-knowledge is focused, and the summary matches what you get after install.
openai-knowledge has been reliable in day-to-day use. Documentation quality is above average for community skills.
openai-knowledge is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added openai-knowledge from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
openai-knowledge fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: openai-knowledge is the kind of skill you can hand to a new teammate without a long onboarding doc.
openai-knowledge fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added openai-knowledge from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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