Official OpenAI skill that tells agents to use the OpenAI developer documentation MCP server first for API, Codex, Apps SDK, model-selection, and migration questions.
Open the source and read safety notes before installing.
Source-backed facts for citing this resource, derived directly from the registry — also available as plain text for AI assistants.
Decision playbook
Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.
0
71
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No baseline selected
No major trust-signal divergence detected in the current selection.
Confirm ownership and provenance before trusting install instructions.
Source link availableRequired
Open the canonical repository and verify ownership.
Source provenance statusRequired
Marked as source-backed.
Metadata reviewed
No reviewed flag detected in metadata.
Validate risk disclosures before installation or API wiring.
Safety notes presentRequired
Review the listed safety guidance before running commands.
Privacy notes presentRequired
Review data handling notes before connecting accounts or secrets.
Trust level risk gateRequired
Trust level does not block evaluation.
Check package metadata and artifact integrity signals.
Install payload available
Install or copy payload is available for review.
Package verification flag
No package verification flag provided.
Checksum metadata
No checksum provided for downloaded artifact.
Use compare context to validate trade-offs before adoption.
Compare tray has multiple entries
Add at least one more entry to compare trust differences.
Baseline comparison available
No baseline peer selected yet.
Diverging trust signals identified
No major trust-signal divergence found.
Setup at a glance
Copy-ready — paste the snippet to get started.
Adoption plan
Current risk score 24/100. Use staged verification before broader rollout.
Validate source and review signals before any execution.
Confirm source provenanceRequired
Source URL/provenance metadata is present.
Confirm metadata review state
No review metadata found; increase manual validation.
Verify install payload
Install/config payload exists and can be inspected.
Confirm safety, privacy, and package integrity signals.
Review safety notesRequired
Safety notes are present.
Review privacy notesRequired
Privacy notes are present.
Verify package integrity metadata
No package verification/checksum metadata.
Adopt in controlled steps based on the selected plan.
Run in isolated sandbox firstRequired
Use a constrained sandbox and observe behavior across multiple tasks.
Roll out graduallyRequired
Roll out to a small cohort before wider usage.
Set monitoring and fallback
Define rollback path and monitor errors after adoption.
Evidence readiness
Missing required evidence: Metadata review. Risk score 31.
Source repository/provenance is listed.
Required in this preset
Review metadata is missing.
Required in this preset
Safety notes are present.
Required in this preset
Privacy notes are present.
Optional in this preset
Package integrity metadata is missing.
Optional in this preset
Install payload is available.
Required in this preset
Required gaps: Metadata review
Decision timeline
Blocking gaps: Check metadata review status. Risk 28.
triage
Source/provenance metadata is available.
triage
Review metadata is missing.
verify
Safety notes are available.
verify
Privacy notes are available.
verify
Package integrity metadata is missing.
rollout
Install payload is available.
Blockers: Check metadata review status
Prerequisite readiness
4 prerequisites to line up before setup.
Safety & privacy surface
3 safety and 3 privacy notes across 4 risk areas. Review closely: credentials & tokens, third-party handling.
| Platform | Support | Install path |
|---|---|---|
| claude-code | Native | .claude/skills/<skill-name>/SKILL.md |
| codex | Native | .agents/skills/<skill-name>/SKILL.md |
| windsurf | Native | .windsurf/skills/<skill-name>/SKILL.md |
| gemini | Native | .gemini/skills/<skill-name>/SKILL.md or .agents/skills/<skill-name>/SKILL.md |
| cursor | Adapter | .cursor/rules/<skill-name>.mdc |
| cli | Manual | AGENTS.md or tool-specific context file |
Use the OpenAI Docs Skill when answering OpenAI product or API questions.
Search and fetch official OpenAI developer docs through the configured
`openaiDeveloperDocs` MCP server first, then fall back only to official
OpenAI domains when the MCP source is unavailable.OpenAI Docs Skill is an official skill from the openai/skills repository. It
helps agents answer OpenAI product and API questions from current official
documentation instead of stale memory. The skill is designed to pair with
OpenAI's public developer documentation MCP server at
https://developers.openai.com/mcp.
Use it when a workflow needs source-backed answers about the OpenAI API, Responses API, ChatGPT Apps SDK, Codex, model selection, model migration, prompt upgrades, Realtime, Agents SDK, or adjacent OpenAI developer surfaces.
AGENTS.md
questions with a source route instead of guessing from memory.This listing does not package a local archive. Use the source repository and your agent's supported skill-install workflow.
codex mcp add openaiDeveloperDocs --url https://developers.openai.com/mcp
https://github.com/openai/skills/tree/main/skills/.curated/openai-docs
SKILL.md-style instructions and call the OpenAI
developer Docs MCP server.AGENTS.md workflows can adapt the
routing rules as durable project instructions when their skill runtime differs.The skill does not authenticate to OpenAI, operate accounts, create keys, or perform production API calls. It is a retrieval and source-priority rule for agents. Keep private data out of documentation searches and verify claims with official docs before changing production code.
Show that OpenAI Docs Skill is listed on HeyClaude. Paste this Markdown into your README — it renders the badge and links back to this page.
[](https://heyclau.de/entry/skills/openai-docs-skill)OpenAI Docs Skill side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.
1 trust signal differ across this comparison (Submitter).
| Field | Official OpenAI skill that tells agents to use the OpenAI developer documentation MCP server first for API, Codex, Apps SDK, model-selection, and migration questions. Open dossier | Google Agent Skills catalog for AI agents working with Google Cloud, Gemini Enterprise Agent Platform, Gemini APIs, Skill Registry, Cloud Run, BigQuery, Firebase, GKE, Cloud SQL, AlloyDB, gcloud, auth, onboarding, and Well-Architected Framework guidance. Open dossier | Official LiveKit Agent Skills for AI coding agents building low-latency voice AI, LiveKit Agents workflows, handoffs, mandatory tests, and simulation scenario suites. Open dossier | Agent Skill from mcp-use for turning OpenAPI or Swagger specs into MCP servers with operation-to-tool mapping, auth wiring, Zod schema generation, inspector testing, and streamable HTTP deployment. Open dossier |
|---|---|---|---|---|
| Next steps | ||||
| Trust | ||||
| Review status | Not reviewed | Not reviewed | Not reviewed | Not reviewed |
| Package trust | Package not verified | Package not verified | Package not verified | Package not verified |
| Source provenance | Source-backed | Source-backed | Source-backed | Source-backed |
| SubmitterDiffers | JSONbored | — | — | — |
| Install risk | Review first | Review first | Review first | Review first |
| Notes | Safety ✓ Privacy ✓ | Safety ✓ Privacy ✓ | Safety ✓ Privacy ✓ | Safety ✓ Privacy ✓ |
| Brand | — | — | ||
| Category | skills | skills | skills | skills |
| Source | Source-backed | Source-backed | Source-backed | Source-backed |
| Author | OpenAI | LiveKit | mcp-use | |
| Added | 2026-06-05 | 2026-06-18 | 2026-06-18 | 2026-06-18 |
| Platforms | ||||
| Harness | ||||
| Source repo | — | — | — | — |
| Safety notes | ✓The skill is read-only guidance; it does not call OpenAI APIs, create API keys, modify accounts, or execute code by itself. Do not use the skill as proof that a model, API parameter, entitlement, or product feature exists; it routes the agent to official docs so the answer can be verified. Keep model upgrade work narrow unless the user explicitly asks for SDK, auth, environment, or provider migration changes. | ✓Google Cloud skills can create, update, delete, deploy, query, or configure cloud resources, datasets, IAM policies, service accounts, APIs, containers, jobs, and networking. The gcloud skill requires command validation and safety guardrails before invoking Google Cloud CLI commands; do not let agents improvise cloud commands from memory. Skill Registry guidance includes skill lifecycle management such as upload, update, and permanent delete operations; validate environment and approval before use. Cloud Run, GKE, BigQuery, Firebase, Cloud SQL, AlloyDB, and Gemini API workflows can create cost, expose endpoints, alter data, or change production behavior. The repository notes active development, so verify exact commands, product names, API availability, and launch-stage limits before production use. | ✓The livekit-agents skill intentionally pushes agents toward implementation work for voice AI systems that can join realtime rooms, call tools, speak to users, and route calls; generated code still needs human review. The skill requires tests for agent behavior, but tests do not prove latency, safety, consent, telephony legality, privacy, or production readiness by themselves. The livekit-simulations skill includes private-beta caveats for simulation commands and requires current CLI help or docs verification before running `lk agent simulate`. Do not let a coding agent invent LiveKit API signatures from memory; the skill repeatedly requires MCP/docs verification because the SDK changes quickly. Voice agent handoffs, tasks, tool calls, and simulation scenarios can influence real user conversations if deployed; validate in staging rooms before production. | ✓Generated MCP tools can expose every selected REST operation from a source API, including destructive or account-changing endpoints if the operation filter is too broad. Large OpenAPI specs can create noisy tool surfaces. Filter by tag or operation list when the API has many endpoints. Auth wiring may include API keys, bearer tokens, basic auth, OAuth bearer tokens, and environment variables; never put secret values in the spec, generated source, prompts, or PR text. The skill recommends streamable HTTP for generated mcp-use servers; review deployment auth, CORS, rate limits, logs, and public reachability before publishing. Human review is needed for generated schemas, tool descriptions, error handling, and write operations before giving an agent access to real accounts. |
| Privacy notes | ✓Documentation queries can reveal what product, API, model, migration, or customer workflow the user is researching. Avoid sending private prompts, customer data, secrets, internal repository names, or unreleased product plans through docs-search queries. Skill text, fetched docs, citations, and agent transcripts can persist in local logs or conversation history depending on the client. | ✓Google Cloud workflows may expose project IDs, service account emails, OAuth tokens, API keys, ADC credentials, Terraform state, dataset names, table schemas, query text, logs, traces, prompts, model outputs, embeddings, and customer data. BigQuery, Firebase, Cloud SQL, AlloyDB, GKE, and Agent Platform workflows may process regulated or proprietary data; review data residency, IAM, retention, audit logging, and sharing rules before use. Gemini API and Agent Platform skills can send prompts, files, images, audio, video, tool inputs, structured outputs, cached contexts, and batch datasets to Google services. Keep credentials, project IDs when sensitive, private queries, logs, trace payloads, Terraform state, customer data, and generated datasets out of public prompts, issues, PRs, and screenshots. | ✓LiveKit voice agent work can involve audio, video, transcripts, room metadata, participant identities, phone call details, test personas, tool inputs, tool outputs, and logs. The skills are prompt/instruction assets, but the implementations they guide may send data to LiveKit, STT providers, LLM providers, TTS providers, MCP servers, telephony providers, and observability backends. Keep LIVEKIT_API_SECRET, provider keys, SIP credentials, room tokens, recordings, transcripts, and generated scenario files containing sensitive business logic out of prompts, public issues, screenshots, and committed configs. The simulations skill says scenario generation reads the user's local agent code and should not upload that code; preserve that local-only boundary when using it. | ✓OpenAPI specs can expose private endpoint names, internal domains, auth schemes, schemas, object fields, customer concepts, and operational workflows. Tool calls can send prompts, arguments, request bodies, auth-scoped API responses, error payloads, and logs through the MCP server, model provider, and deployment platform. Keep API keys, tokens, OAuth secrets, cookies, private base URLs, customer data, and internal spec comments out of public examples, repository files, issue comments, and screenshots. For third-party or customer APIs, confirm data retention and logging behavior across the MCP client, mcp-use deployment target, model provider, and API provider. |
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| Config | — | — | — | — |
| Citations | ||||
| Claim | Unclaimed | Unclaimed | Unclaimed | Unclaimed |
Google product skills for Claude Code, Codex, Gemini CLI, and other agents covering Agent Platform, Gemini API, Cloud Run, BigQuery, Firebase, GKE, and gcloud workflows.
LiveKit skill pack for voice AI architecture, handoffs, testing discipline, and simulation scenarios for Claude Code, Codex, Cursor, and other agents.
mcp-use skill for wrapping OpenAPI and Swagger specs as MCP tools with mechanical schema mapping, auth wiring, tests, and deployment guidance.
Source-backed guides for putting this to work.
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