openai-docs
Use when the user asks how to build with OpenAI products or APIs, asks about Codex itself or choosing Codex surfaces, needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; use OpenAI docs MCP tools for non-Codex docs questions, use the Codex manual helper first for broad Codex self-knowledge, and restrict fallback browsing to official OpenAI domains.
git clone --depth 1 https://github.com/deonmenezes/mantishack /tmp/openai-docs && cp -r /tmp/openai-docs/codex-rs/skills/src/assets/samples/openai-docs ~/.claude/skills/openai-docsSKILL.md
# OpenAI Docs Provide authoritative, current guidance from OpenAI developer docs using the developers.openai.com MCP server. "Docs MCP" means `mcp__openaiDeveloperDocs__search_openai_docs` and `mcp__openaiDeveloperDocs__fetch_openai_doc`; for API reference, schema, parameter, or required-field questions, also use `mcp__openaiDeveloperDocs__get_openapi_spec` when available. Official-domain web search is fallback after those tools are unavailable or unhelpful. Broad Codex questions use the manual helper before Docs MCP. This skill also owns model selection, API model migration, and prompt-upgrade guidance. ## API Key Setup For requests to build, run, configure, debug, or implement an API-backed app, script, CLI, generator, or tool, use `openai-platform-api-key` first when available. After that credential gate is resolved, return here for current docs as needed. Use this skill directly for docs-only questions, citations, model/API guidance, conceptual explanations, and examples that do not require building or running an API-backed artifact. ## Workflow Configuration ### Source Priority - For Codex self-knowledge, use the Codex source route below; it owns when to use the manual helper, Docs MCP, or bounded uncertainty. - For non-Codex OpenAI docs questions, use `mcp__openaiDeveloperDocs__search_openai_docs` to find the most relevant doc pages. - For non-Codex OpenAI docs questions, fetch the relevant page with `mcp__openaiDeveloperDocs__fetch_openai_doc` before answering. If search is noisy, run a narrower Docs MCP search; when any plausible official OpenAI docs URL is known or found, try fetching that URL through Docs MCP before relying on web-search content. - For API reference, schema, parameter, or required-field questions, use `mcp__openaiDeveloperDocs__get_openapi_spec` when available to verify the API shape alongside the relevant guide or reference page. - Use `mcp__openaiDeveloperDocs__list_openai_docs` only when you need to browse or discover non-Codex pages without a clear query. - For model-selection, "latest model", or default-model questions, fetch `https://developers.openai.com/api/docs/guides/latest-model.md` first. If that is unavailable, load `references/latest-model.md`. - For model upgrades or prompt upgrades, run `node scripts/resolve-latest-model-info.js` only when the target is latest/current/default or otherwise unspecified; otherwise preserve the explicitly requested target. - Preserve explicit target requests: if the user names a target model like "migrate to GPT-5.4", keep that requested target even if `latest-model.md` names a newer model. Mention newer guidance only as optional. - If current remote guidance is needed, fetch both the returned migration and prompting guide URLs directly. If direct fetch fails, use MCP/search fallback; if that also fails, use bundled fallback references and disclose the fallback. ## OpenAI product snapshots 1. Apps SDK: Build ChatGPT apps by providing a web component UI and an MCP server that exposes your app's tools to ChatGPT. 2. Responses API: A unified endpoint designed for stateful, multimodal, tool-using interactions in agentic workflows. 3. Chat Completions API: Generate a model response from a list of messages comprising a conversation. 4. Codex: OpenAI's coding agent for software development that can write, understand, review, and debug code. 5. gpt-oss: Open-weight OpenAI reasoning models (gpt-oss-120b and gpt-oss-20b) released under the Apache 2.0 license. 6. Realtime API: Build low-latency, multimodal experiences including natural speech-to-speech conversations. 7. Agents SDK: A toolkit for building agentic apps where a model can use tools and context, hand off to other agents, stream partial results, and keep a full trace. ## Codex self-knowledge Use this path for questions about Codex itself: configuring, extending, operating, troubleshooting, local state, product surfaces, or where Codex behavior should live. A codebase merely mentioning a plugin, skill, hook, MCP server, browser, or automation is not enough. For generic software tasks, answer the software task directly; if asked whether Codex self-knowledge applies, answer that meta question briefly and continue the requested artifact. ### Source Route The Codex manual is the first source for broad Codex synthesis. Treat the manual and Docs MCP as different lanes, not interchangeable official-doc sources. For published-user Codex product answers, the source route is complete: the manual, Docs MCP when this route calls for it, official OpenAI web fallback, and callable capabilities surfaced in the current session when the question is about that capability. Knowledge bases outside developers.openai.com are outside this route for public product answers. For broad Codex behavior, setup, customization, skills, plugins, MCP, hooks, `AGENTS.md`, automations, surfaces, local state, or system-map questions: 1. Reuse a same-thread manual and outline path when it is still fresh. 2. Otherwise run the skill-local helper first in normal writable sessions. Skip it without trying only when the session is explicitly read-only, shell execution is unavailable, or visible policy shows no allowed temp cache. 3. By default, the helper chooses the first usable temp cache dir in this order: `$TMPDIR/openai-docs-cache`, `%TEMP%\openai-docs-cache`, `%TMP%\openai-docs-cache`, `/private/tmp/openai-docs-cache`, then `/tmp/openai-docs-cache`. Workspace-only write access is not enough for this temp cache. 4. Run the helper directly unless you need to override the cache dir. The helper falls back to `curl` when native `fetch` is unavailable or when proxy env vars are present, so no shell-specific proxy prefix is required. Resolve `<skill-dir>` to this skill's actual directory; in copied local eval workdirs this is usually `.codex/skills/openai-docs`: ```bash node <skill-dir>/scripts/fetch-codex-manual.mjs ``` If you need to override the cache dir, pass `--cache-dir <cache-dir>`. O
Use this agent when the target is a LIVE REST or GraphQL API you are authorized to test and the question is "can I tamper request bodies, headers, ids, and tokens to read or act on data that isn't mine?" — active, request-driven abuse of the API contract, not static code review. It drives REAL HTTP at the endpoints: BOLA/IDOR object-id enumeration (increment/swap/UUID-shuffle the id and diff the access decision), broken function-level authz (replay an admin verb/path with a low-priv token), mass-assignment (inject role/is_admin/is_verified/owner_id into the JSON body), excessive-data-exposure (the response over-returns fields the UI never shows), GraphQL introspection + alias/batch amplification + nested-query DoS, content-type and HTTP-verb tampering (POST→PUT/PATCH/DELETE, application/json→text/plain→x-www-form-urlencoded), JWT/session/token swap across two users, and rate-limit / idempotency-key bypass. It proves every finding with a behavioral oracle — a status/length/timing/field-set diff between the authorized baseline and the tampered request — never a guess. Prefer this agent over a code reader when you hold a base URL or a schema and want to mutate live traffic methodically.\n\n<example>\nContext: The user has a running API with numeric resource ids and two test accounts.\nuser: "Here's our staging API at https://api.staging.acme.test and tokens for user A and user B — can user A read user B's orders?"\nassistant: "That's textbook BOLA: same endpoint, swap the object id (or the bearer token) and diff the access decision. I'll use the Task tool to launch the api-abuse-fuzzer agent to enumerate /orders/{id} with A's token against B's ids and prove the cross-tenant read with a status + ownership-field oracle."\n<agent_launch>\nDelegating to api-abuse-fuzzer: a live authorized API + two tokens + object-id enumeration is its core BOLA/IDOR mission.\n</agent_launch>\n</example>\n\n<example>\nContext: The user exposes a GraphQL endpoint and isn't sure introspection or query batching is locked down.\nuser: "Our /graphql is behind auth but I want to know if a low-priv user can pull admin fields, brute force via aliases, or knock it over with a deep nested query."\nassistant: "GraphQL abuse surface: introspect the schema, alias-batch a login/lookup to bypass per-request rate limits, and send a bounded cyclic nested query as a timing oracle. I'll launch the api-abuse-fuzzer agent to tamper the operation and measure the depth/timing oracle."\n<agent_launch>\nDelegating to api-abuse-fuzzer for GraphQL introspection, alias/batch amplification, and nested-query DoS against the live endpoint.\n</agent_launch>\n</example>\n\nProactively suggest using this agent when: a live base URL + an OpenAPI/Swagger/GraphQL schema (or a captured request) is in hand and the target is authorized in-scope; endpoints take a resource identifier in the path/query/body (/users/{id}, ?account=, {"order_id": ...}) — BOLA/IDOR territory; the user holds 2+ accounts or tokens (low-priv + high-priv, tenant A + tenant B) to run an authorization differential; there are admin/privileged verbs (DELETE, PUT /admin/*, role-changing mutations) and you want to hit them as a non-admin; a write endpoint accepts a JSON object — test mass-assignment of role/is_admin/verified/balance/owner_id; a /graphql endpoint exists (introspection, alias/batch abuse, nested-query DoS, field-level authz); or the user mentions rate limiting, coupon/OTP brute force, idempotency keys, BOLA, BFLA, mass assignment, or "excessive data exposure".
Use this agent when a codebase, PR, or service needs its IMPLICIT TRUST ASSUMPTIONS enumerated and attacked — every place the code silently trusts a header, an "internal-only" route, an "already-validated-upstream" input, an ID that "belongs to the caller," or a value that "can't be null/negative." It specializes in confused-deputy (CWE-441), mass-assignment (CWE-915), input-validation gaps (CWE-20), and second-order/stored injection (CWE-89/CWE-79). This is the agent for trust-boundary audits, multi-service request paths, ORM/serializer review, and proxy/gateway/header-forwarding code.\n\n<example>\nContext: User has a multi-service backend where an edge proxy forwards auth context downstream.\nuser: "Our gateway sets X-User-Id from the JWT and the internal services read it to authorize. Can you check this?"\nassistant: "This is a classic confused-deputy / trust-boundary surface — the downstream services trust a header they can't verify. I'll use the Task tool to launch the assumption-pressure-test agent to enumerate every internal endpoint that reads X-User-Id and prove whether an attacker can reach it directly and forge it."\n<agent_launch>\nDelegating to assumption-pressure-test: the request hinges on an implicit 'this header is trusted because the gateway set it' assumption that must be attacked.\n</agent_launch>\n</example>\n\n<example>\nContext: User just merged an ORM update endpoint.\nuser: "Here's the new profile update handler: User.objects.filter(id=request.user.id).update(**request.data)"\nassistant: "That `**request.data` spread is a mass-assignment sink — it trusts that the request body only contains the fields you intended. I'll launch the assumption-pressure-test agent to map which model columns (is_admin, balance, role) become attacker-writable and confirm reachability."\n<agent_launch>\nDelegating to assumption-pressure-test for the CWE-915 mass-assignment and the implicit 'the body only has safe fields' assumption.\n</agent_launch>\n</example>\n\nProactively suggest using this agent when:\n- Code reads request headers (X-Forwarded-For, X-User-Id, X-Real-IP, X-Internal-*, Host) for trust or authorization decisions\n- A serializer/ORM uses bulk binding: `**req.body`, `Object.assign`, `ModelMapper`, `BeanUtils.copyProperties`, `update_attributes`, `params.permit!`\n- Comments or names assert trust: "internal only", "already validated", "trusted", "comes from gateway", "sanitized upstream"\n- Data is stored then later concatenated into SQL/HTML/shell (second-order injection)\n- An endpoint takes an `id`/`uuid`/`account`/`order` param that maps to a resource (IDOR / object ownership)
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