OpenAI Cookbook recently launched the "GPT-5.1-Codex-Max Prompting Guide", which systematically sorts out the model's prompt design paradigm in agent and developer tool scenarios. The document positions Codex-Max as an "intelligent asana coding" model, emphasizing the use of fine system prompts and tool conventions to guide it through multi-step modifications, debugging, and refactoring in the real codebase, and deeply integrating with the Responses API.
The guide extensively describes the recommended system prompt structure, including requiring the model to prioritize correctness and stability with a "rigorous engineer" mentality, avoiding broad try/catch, silent failures, and arbitrary type assertions, and encouraging full context reading and batch editing of logical revisions before modification. The documentation also clarifies editing constraints: prefer to use apply_patch for single-file updates, do not roll back unrequested changes, do not use dangerous git commands, and stop and ask the user immediately if there is an unexpected file change.
In terms of tool usage, the guidance recommends reading files and search results in parallel through multi_tool_use.parallel, reducing serial calls, and providing examples of standard definitions for tools such as apply_patch, shell_command, and update_plan. The document also describes the /responses/compact context compression mechanism to preserve critical information in long conversations and long link tasks. It also emphasizes that the Codex series utilizes "inference summaries" to show users Midjourney plans, which are partially generated by independent models without manual intervention in prompts. Overall, the guide provides a relatively complete engineering practice template for building IDE plugins and code agents based on GPT-5.1-Codex-Max.
Frequently Asked Questions
Q: Who is this Prompting Guide for?
A: Mainly for developers and teams who want to integrate GPT-5.1-Codex-Max in their IDEs, CLIs, or self-built agents for designing system prompts and tool protocols.
Q: Why does the guide emphasize the use of apply_patch?
A: Because the model is specially trained for this diff format, it can generate applicable patches more consistently, reducing the risk of accidental code deletion or format confusion.
Q: What is the role of multi_tool_use.parallel?
A: It is used to package and execute multiple file reading, searching, and other operations in parallel, reducing the number of round trips and improving efficiency and stability in complex tasks.
Q: When is /responses/compact context compression used?
A: When the conversation and tool call history is close to the upper limit of context, a compressed version can be generated through this endpoint, allowing long tasks to continue without losing key information.
Q: What are the security requirements for shell use in the guide?
A: It is recommended to execute commands through restricted shell_command tools to clarify workdir, timeouts, and whether privileges need to be escalated, and it is strictly forbidden to directly use dangerous git or system-disruptive operations.
