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Gpt 5 4 prompting

Skill carolafortified787/codex-plugin-cc/plugins/codex/skills/gpt-5-4-prompting

Internal guidance for composing Codex and GPT-5.4 prompts for coding, review, diagnosis, and research tasks inside the Codex Claude Code pluginFrom its SKILL.md

Install
npx -y skills add carolafortified787/codex-plugin-cc --skill gpt-5-4-prompting

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

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  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

3.6 KB, 730 tokens by cl100k_base, as published. Nobody here has run it

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.

What ships with it: 3 files

9.6 KB alongside SKILL.md

Gives 0 of the 12 instructions most prompt engineering skills give in 730 tokens

Counted across 542 of the 575 authors here whose files we hold, read 2026-09-06

  • Provide few-shot examples for complex tasksin 17 of 542, across 16 files
  • Ask clarifying questions if information is ambiguousin 16 of 542, across 14 files
  • Output a complete optimized prompt for the userin 15 of 542, across 9 files
  • Validate structured outputs against schemasin 15 of 542, across 13 files
  • Analyze the draft prompt for intent and gapsin 14 of 542, across 8 files
  • Detect project tech stack from local filesin 14 of 542, across 8 files
  • Recommend a model based on task scopein 13 of 542, across 7 files
  • Present results in the specified output formatin 13 of 542, across 7 files
  • Match intent and scope to ECC componentsin 13 of 542, across 7 files
  • Ask one question at a timein 13 of 542, across 12 files
  • Respond in the same language as the user inputin 12 of 542, across 6 files
  • Ask up to three clarification questions if context is missingin 11 of 542, across 5 files

Said here and by no other author read

  • Tighten verification rules before escalating complexity

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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