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OpenAI Codex Prompting Guide for gpt-5.3-codex

Summary

OpenAI's official prompting guide for gpt-5.3-codex is the closest analogue OpenAI has to the patterns V025 builds around CLAUDE.md and the skill system. AGENTS.md ≈ CLAUDE.md (merged top-down from home dir + repo path). apply_patch ≈ our Edit/Write tool contract. The guide's "senior engineer" principle is a single sentence doing the work of dozens of "do X / don't do Y" rules — direct corroboration of the Anthropic 7-lessons paper captured the same day.

Key Details

  • AGENTS.md is OpenAI's CLAUDE.md. Codex-cli auto-discovers AGENTS.md from home dir and the repo path. Later directories override earlier ones; each merged file is injected as a separate user-role message prefixed with directory context.
  • Senior-engineer principle (single sentence, replaces a checklist). "Function as a senior engineer—after receiving direction, independently gather context, plan, implement, verify, and refine without awaiting incremental prompts." Default toward implementation with reasonable assumptions over clarification requests.
  • apply_patch is the recommended tool. First-class Responses API support or context-free grammar freeform tools; matches the model's training distribution. Direct parallel to our Edit-over-shell rule.
  • Compaction unlocks multi-hour reasoning. /compact returns encrypted_content for subsequent requests; pass compacted items forward, retaining key state with reduced tokens. Comparable in goal to our SPEC-141 state-drift / context-restoration work.
  • Phase parameter prevents early stopping. null / "commentary" / "final_answer" on assistant items; preserving phase metadata during history reconstruction is critical for performance.
  • Preamble messages — one-sentence acknowledgement + brief planning statement, every 1–3 execution steps, minimum every 6 steps or 10 tool calls. Almost identical to our "narration vs. silence" rule.
  • Two personality presets. Friendly (supportive, "we" language, onboarding) vs. Pragmatic (terse, throughput-focused, expert users). Worth comparing to our voice/tone in /vt-c-visitrans-design-system.
  • Parallel tool calling. parallel_tool_calls: true triggers explicit batch-planning instructions; ordering must group function_calls with corresponding outputs in history.
  • Response truncation budget. Limit tool outputs to ~10k tokens (~bytes/4); when over, allocate half to start / half to end and truncate the middle with a placeholder.

Why Rolf Thinks This Matters

Further Reading