Agent skill

openai-docs

Access OpenAI developer documentation via Context7 MCP. Provides up-to-date docs for Codex CLI, OpenAI API, Python/Node SDKs, Agents SDK, and MCP configuration. Use when: (1) configuring Codex CLI or MCP servers, (2) writing OpenAI API integrations, (3) building agents with OpenAI SDKs, (4) troubleshooting Codex execution. Triggers: 'openai docs', 'codex documentation', 'openai api reference', 'codex mcp', 'agents sdk'.

Stars 115
Forks 18

Install this agent skill to your Project

npx add-skill https://github.com/alfredolopez80/multi-agent-ralph-loop/tree/main/.claude/skills/openai-docs

SKILL.md

OpenAI Documentation Access Skill

v2.88 Key Changes (MODEL-AGNOSTIC)

  • Model-agnostic: Uses model configured in ~/.claude/settings.json or CLI/env vars
  • No flags required: Works with the configured default model
  • Flexible: Works with GLM-5, Claude, Minimax, or any configured model
  • Settings-driven: Model selection via ANTHROPIC_DEFAULT_*_MODEL env vars

ultrathink - Take a deep breath. We're not here to write code. We're here to make a dent in the universe.

The Vision

Documentation lookups should feel inevitable and authoritative.

Your Work, Step by Step

  1. Identify target: Pick the right library and query.
  2. Resolve ID: Use Context7 to get exact docs.
  3. Query precisely: Ask for focused, answerable snippets.
  4. Apply results: Convert docs into actionable guidance.

Ultrathink Principles in Practice

  • Think Different: Seek the most direct source of truth.
  • Obsess Over Details: Use exact IDs and query wording.
  • Plan Like Da Vinci: Decide the lookup path before querying.
  • Craft, Don't Code: Keep results concise and relevant.
  • Iterate Relentlessly: Re-query when ambiguity remains.
  • Simplify Ruthlessly: Avoid unnecessary sources.

OpenAI Documentation Access Skill

Access OpenAI's complete developer documentation through Context7 MCP integration.

Quick Start

yaml
# Query Codex CLI documentation
mcp__context7__query-docs:
  libraryId: "/websites/developers_openai_codex"
  query: "your question about Codex CLI"

# Query OpenAI API documentation
mcp__context7__query-docs:
  libraryId: "/websites/platform_openai"
  query: "your question about OpenAI API"

Available Documentation Libraries

Library ID Content Snippets Score
/websites/developers_openai_codex Codex CLI docs 614 75.8
/websites/platform_openai OpenAI API docs 9,418 69.1
/openai/openai-python Python SDK 429 90.7
/openai/openai-node Node.js SDK 437 87.9
/openai/codex Codex core 491 62.1
/openai/codex-action GitHub Action 36 78.8

Common Queries

Codex CLI Configuration

yaml
# MCP server configuration
query-docs:
  libraryId: "/websites/developers_openai_codex"
  query: "MCP server configuration config.toml remote URL authentication"

# Sandbox modes and permissions
query-docs:
  libraryId: "/websites/developers_openai_codex"
  query: "sandbox modes read-only workspace-write danger-full-access"

# Session resume and parallel execution
query-docs:
  libraryId: "/websites/developers_openai_codex"
  query: "exec resume session parallel execution workflow"

OpenAI API Integration

yaml
# Chat completions
query-docs:
  libraryId: "/websites/platform_openai"
  query: "chat completions API streaming function calling"

# Embeddings and vector search
query-docs:
  libraryId: "/websites/platform_openai"
  query: "embeddings API text-embedding-3 vector dimensions"

# Assistants API
query-docs:
  libraryId: "/websites/platform_openai"
  query: "assistants API threads messages runs tools"

SDK Usage

yaml
# Python SDK async patterns
query-docs:
  libraryId: "/openai/openai-python"
  query: "async client streaming completions error handling"

# Node.js SDK TypeScript
query-docs:
  libraryId: "/openai/openai-node"
  query: "TypeScript types streaming response handling"

MCP Configuration Reference

Context7 (Already Configured)

toml
# ~/.codex/config.toml
[mcp_servers.context7]
command = "npx"
args = ["-y", "@upstash/context7-mcp@latest"]

Remote MCP Servers

toml
# Streamable HTTP server format
[mcp_servers.example]
url = "https://example.com/mcp"
bearer_token_env_var = "EXAMPLE_TOKEN"
http_headers = { "X-Custom-Header" = "value" }

STDIO Servers

toml
# Local command-based server
[mcp_servers.local]
command = "npx"
args = ["-y", "@package/mcp-server"]

[mcp_servers.local.env]
API_KEY = "your-key"

Integration with Codex CLI Skill

This skill complements /codex-cli by providing documentation lookup:

  1. Before execution: Query docs for correct flags/options
  2. On error: Look up error codes and solutions
  3. Configuration: Find correct config.toml syntax

Workflow Example

bash
# 1. Query documentation for correct syntax
# Use mcp__context7__query-docs with libraryId="/websites/developers_openai_codex"

# 2. Execute Codex with correct options
codex exec -m gpt-5.2-codex --full-auto "task"

# 3. On error, query docs for solution
# Query: "error code XYZ troubleshooting"

Claude-Codex Documentation Bridge

When Claude needs OpenAI documentation:

  1. Use Context7 MCP (already available in both Claude and Codex)
  2. Query appropriate library based on topic
  3. Apply findings to implementation

This eliminates the need for a separate "openaiDevelopers" MCP - Context7 provides all OpenAI documentation with 614+ Codex CLI snippets and 9,400+ API snippets.

See Also

  • /codex-cli - Codex CLI orchestration skill
  • /library-docs - General library documentation via Context7
  • ~/.codex/config.toml - MCP server configuration

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