Artificial intelligence · llms.txt file breakdown
Complete documentation hub for OpenAI API, Ads, Sign in with ChatGPT, Plugins, Workspace Agents, Codex, Agentic Commerce, the developer blog, Cookbook, learning resources, and learning tracks.
The actual file
The saved llms.txt text, displayed as source. The file belongs to its publisher; the live endpoint may change.
Complete saved Markdown shown below.
# OpenAI Developers
> Complete documentation hub for OpenAI API, Ads, Sign in with ChatGPT, Plugins, Workspace Agents, Codex, Agentic Commerce, the developer blog, Cookbook, learning resources, and learning tracks.
Start with the product index that matches your task. Product indexes route to detailed pages; documentation indexes also provide Markdown pages and full-document exports.
## Documentation sets
- [OpenAI API guides and reference](https://developers.openai.com/api/llms.txt): Quickstart, Responses API, text and image generation, audio, Realtime and WebRTC, tools and function calling, evals, fine-tuning, models, and endpoint reference.
- [Ads API and campaign documentation](https://developers.openai.com/ads/llms.txt): Partner setup, campaigns, targeting, creatives, product feeds, conversions, measurement, and Ads API reference.
- [Sign in with ChatGPT](https://developers.openai.com/siwc/llms.txt): Quickstart, website and ChatGPT plugin integration, token sharing for open-source clients, and client ID registration.
- [ChatGPT plugins and Apps SDK](https://developers.openai.com/plugins/llms.txt): Build plugins with MCP servers, tools, UI components, authentication, metadata, testing, deployment, review, and submission.
- [Workspace Agents API](https://developers.openai.com/workspace-agents/llms.txt): Authenticate API calls, trigger published workspace agent runs, and inspect run results.
- [Codex developer tools](https://developers.openai.com/codex/llms.txt): Codex CLI, IDE, cloud, config.toml, authentication, customization, automation, and security.
- [ChatGPT product documentation](https://learn.chatgpt.com/llms.txt): ChatGPT Work, administration, collaboration, and product guidance.
- [Agentic Commerce Protocol](https://developers.openai.com/commerce/llms.txt): Merchant onboarding, product feeds, checkout sessions, delegated payments, and production guidance.
- [OpenAI developer blog](https://developers.openai.com/blog/llms.txt): Engineering articles, product launches, technical deep dives, and developer announcements.
- [OpenAI Cookbook examples](https://developers.openai.com/cookbook/llms.txt): Practical code examples and patterns for APIs, agents, evals, multimodal applications, and integrations.
- [Learning resources](https://developers.openai.com/learn/llms.txt): Videos, guides, and conceptual learning material for OpenAI developers.
- [OpenAI developer showcase](https://developers.openai.com/showcase/llms.txt): Projects, demos, games, and applications built with OpenAI APIs and Codex.
## Common tasks
- [OpenAI API quickstart](https://developers.openai.com/api/docs/quickstart.md): Make your first API request with the OpenAI SDK and Responses API.
- [Sign in with ChatGPT quickstart](https://developers.openai.com/siwc/quickstart.md): Add ChatGPT sign-in to your application.
- [Plugin submission guide](https://developers.openai.com/plugins/deploy/submission.md): Prepare, review, submit, and publish a ChatGPT plugin.
- [Image generation guide](https://developers.openai.com/api/docs/guides/image-generation.md): Generate and edit images with OpenAI image models and the API.
- [Create a response API reference](https://developers.openai.com/api/reference/resources/responses/methods/create.md): Parameters and response schema for the Responses API create method.
- [Evals guide](https://developers.openai.com/api/docs/guides/evals.md): Measure and improve model and application quality with OpenAI evals.
- [Function calling guide](https://developers.openai.com/api/docs/guides/function-calling.md): Define tools and handle model requests to call application functions.
- [Cookbook image evals](https://developers.openai.com/cookbook/examples/multimodal/image_evals.md): Build evals for image generation and editing applications.
- [Realtime API with WebRTC](https://developers.openai.com/api/docs/guides/voice-webrtc.md): Connect browser and client applications to the Realtime API.
- [Plugins and Apps SDK quickstart](https://developers.openai.com/plugins/build/app-quickstart.md): Build an MCP server with tools and an optional ChatGPT interface.
- [Trigger workspace agent runs](https://developers.openai.com/workspace-agents/trigger-runs.md): Start ChatGPT workspace agents from backend systems and automations.
- [Ads API quickstart](https://developers.openai.com/ads/api-quickstart.md): Launch your first Ads API workflow.
- [Agentic checkout specification](https://developers.openai.com/commerce/specs/checkout.md): Implement the Agentic Commerce checkout flow.
- [Codex configuration reference](https://developers.openai.com/codex/config-file/config-reference.md): Look up Codex config.toml and requirements.toml settings.
- [Codex CLI customization](https://developers.openai.com/codex/cli-customization.md): Customize the terminal interface, editor, completions, and shortcuts.
## Site navigation
- [OpenAI Developers](https://developers.openai.com/): Developer documentation and resources from OpenAI.
- [ChatGPT developer resources](https://developers.openai.com/chatgpt)
- [Learning tracks](https://developers.openai.com/tracks.md)
- [Showcase](https://developers.openai.com/showcase): Examples built with OpenAI APIs and Codex.
- [Community](https://developers.openai.com/community): Programs, meetups, and support for OpenAI developers.
- [Codex Ambassadors](https://developers.openai.com/community/codex-ambassadors)
- [Codex for Open Source](https://developers.openai.com/community/codex-for-oss)
- [Community hackathons](https://developers.openai.com/community/hackathons)
- [Community events on Luma](https://luma.com/codex-community?utm_source=oaidevs)
- [Codex for Students](https://developers.openai.com/community/students)
## Learning tracks
- [AI app development: Concept to production](https://developers.openai.com/tracks/ai-application-development.md): Build, deploy, and optimize AI apps.
- [Building agents](https://developers.openai.com/tracks/building-agents.md): Learn how to build agents: Foundational concepts to practical implementation
- [Model optimization](https://developers.openai.com/tracks/model-optimization.md): Fine-tune, distill, and optimize models for the best performance and cost.
Measured from the saved file
Size measures the captured UTF-8 text, not compressed transfer size. Tokens are counted with a named tokenizer; other models can count differently. Neither measure establishes context compatibility or answer quality.
Complete documentation hub for OpenAI API, Ads, Sign in with ChatGPT, Plugins, Workspace Agents, Codex, Agentic Commerce, the developer blog, Cookbook, learning resources, and learning tracks.
Context architecture
4 H2 sections organize 40 parsed Markdown links. 19 links point to .md or .markdown paths; 2 link occurrences use another hostname. Linked destinations have not been recursively validated.
| H2 section | Links | UTF-8 bytes | Tokens |
|---|---|---|---|
| Documentation setsLine 7 | 12 | 2137 | 476 |
| Common tasksLine 21 | 15 | 2293 | 508 |
| Site navigationLine 38 | 10 | 840 | 204 |
| Learning tracksLine 50 | 3 | 466 | 101 |
12 distinct links point to other llms.txt paths. These are routes to more indexes, not proof their contents were included in this file.
Link counts exclude parsed fenced and inline code and resolve relative destinations against the final endpoint. Section sizes cover the text below each H2 until the next H2.
Embedded material
Embedded example text and links to further documentation are counted separately. A code block does not establish that a sample runs or that an authentication flow succeeds.
Publisher prioritization
No H2 section named “Optional” was detected in this file.
The community proposal uses Optional by convention for secondary links that can be skipped for a shorter context. This label does not establish that everything outside it is critical, or that the material inside it is deprecated.
Machine-readable routes
MCP-related text was detected in the captured file. 0 links have MCP-related labels or paths. 0 fenced lines match mcpServers, mcp_servers or an mcp add command.
These are text and link observations. No MCP server connection, authentication or tool call was tested.
Index and bundle
Verified text companion
A verified text response establishes a companion at the checked URL. It does not prove the bundle contains all product documentation, that generation is automated, or that it fits an assistant’s context window.
Change evidence
This capture establishes a baseline. Update frequency cannot be determined from one observation.
File changes can reveal documentation edits or navigation changes. They do not by themselves measure product release velocity, accuracy, agent adoption or AI visibility.
b40e651d5d657741912bbbe1696644c295190d46e6f74c089b93f8c98de53e28Counts use a deterministic parser, not a spec-compliance grade. Unusual Markdown and indented code can fall outside its recognized patterns. See the llms.txt proposal and tokenizer implementation.