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GPT-5.4 Prompting

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Optimize prompts for Codex and GPT-5.4 workflows.

by openai31.7k stars on openai/codex-plugin-cc
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Updated Jul 8, 2026
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What GPT-5.4 Prompting does

The GPT-5.4 Prompting skill provides structured guidance for effectively composing prompts for Codex and GPT-5.4-based tasks. This skill is designed for developers and designers who want to maximize the efficiency and accuracy of their interactions with AI coding agents. By following the core principles outlined in this skill, users can ensure that their prompts are concise, well-structured, and tailored to elicit the desired responses from the AI.

This skill emphasizes the importance of clarity and precision in prompt construction. It encourages users to break down complex tasks into simpler, manageable components, ensuring that each prompt focuses on a single clear task. The use of XML tags to define the structure of the prompt allows for a consistent and stable format, which is crucial for maintaining the integrity of the interaction with the AI. By stating the task explicitly and defining what a successful output looks like, users can significantly reduce the chances of misinterpretation by the AI.

Additionally, the skill includes a series of best practices for different scenarios, such as coding, debugging, and research tasks. By incorporating specific blocks for verification and grounding, users can enhance the reliability of the AI's outputs, particularly in high-stakes situations where accuracy is critical. The references provided in the skill offer reusable blocks and templates that can streamline the prompt creation process, making it easier to implement these strategies in everyday workflows.

Overall, the GPT-5.4 Prompting skill is a valuable resource for anyone looking to improve their prompt engineering skills when working with Codex and GPT-5.4. It provides clear, actionable advice that can lead to more effective and productive interactions with AI agents, ultimately enhancing the quality of the coding and research outcomes.

When to use it

Use this skill when you need to prompt Codex or GPT-5.4 for coding, review, diagnosis, or research tasks.

When not to use it

This skill is not suitable for tasks that require extensive natural language dialogue or complex reasoning beyond prompt structuring.

What you can build with it

Improving Coding Prompts

When writing prompts for coding tasks, use this skill to ensure clarity and structure, leading to better AI-generated code.

Debugging Assistance

Utilize the skill's guidelines to create prompts that help Codex diagnose issues effectively, ensuring accurate troubleshooting.

Research Tasks

In research scenarios, apply the skill to form prompts that require citation and grounding, enhancing the reliability of AI responses.

How to install GPT-5.4 Prompting

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1. Install with the skills CLI

npx skills add openai/codex-plugin-cc/gpt-5-4-prompting --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by openai

GPT-5.4 Prompting

Use this skill when codex:codex-rescue needs to ask Codex or another GPT-5.4-based workflow for help.

Prompt Codex like an operator, not a collaborator. Keep prompts compact and block-structured with XML tags. State the task, the output contract, the follow-through defaults, and the small set of extra constraints that matter.

Core rules:

  • Prefer one clear task per Codex run. Split unrelated asks into separate runs.
  • Tell Codex what done looks like. Do not assume it will infer the desired end state.
  • Add explicit grounding and verification rules for any task where unsupported guesses would hurt quality.
  • Prefer better prompt contracts over raising reasoning or adding long natural-language explanations.
  • Use XML tags consistently so the prompt has stable internal structure.

Default prompt recipe:

  • <task>: the concrete job and the relevant repository or failure context.
  • <structured_output_contract> or <compact_output_contract>: exact shape, ordering, and brevity requirements.
  • <default_follow_through_policy>: what Codex should do by default instead of asking routine questions.
  • <verification_loop> or <completeness_contract>: required for debugging, implementation, or risky fixes.
  • <grounding_rules> or <citation_rules>: required for review, research, or anything that could drift into unsupported claims.

When to add blocks:

  • Coding or debugging: add completeness_contract, verification_loop, and missing_context_gating.
  • Review or adversarial review: add grounding_rules, structured_output_contract, and dig_deeper_nudge.
  • Research or recommendation tasks: add research_mode and citation_rules.
  • Write-capable tasks: add action_safety so Codex stays narrow and avoids unrelated refactors.

How to choose prompt shape:

  • Use built-in review or adversarial-review commands when the job is reviewing local git changes. Those prompts already carry the review contract.
  • Use task when the task is diagnosis, planning, research, or implementation and you need to control the prompt more directly.
  • Use task --resume-last for follow-up instructions on the same Codex thread. Send only the delta instruction instead of restating the whole prompt unless the direction changed materially.

Working rules:

  • Prefer explicit prompt contracts over vague nudges.
  • Use stable XML tag names that match the block names from the reference file.
  • Do not raise reasoning or complexity first. Tighten the prompt and verification rules before escalating.
  • Ask Codex for brief, outcome-based progress updates only when the task is long-running or tool-heavy.
  • Keep claims anchored to observed evidence. If something is a hypothesis, say so.

Prompt assembly checklist:

  1. Define the exact task and scope in <task>.
  2. Choose the smallest output contract that still makes the answer easy to use.
  3. Decide whether Codex should keep going by default or stop for missing high-risk details.
  4. Add verification, grounding, and safety tags only where the task needs them.
  5. Remove redundant instructions before sending the prompt.

Reusable blocks live in references/prompt-blocks.md. Concrete end-to-end templates live in references/codex-prompt-recipes.md. Common failure modes to avoid live in references/codex-prompt-antipatterns.md.

Frequently asked questions about GPT-5.4 Prompting

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