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Gpt 5 4 prompting

Skill nota-america/forgecat-agent-profiles/profiles/openai/codex-plugin-cc/openai_codex-plugin-cc_codex/for-forgecat/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 nota-america/forgecat-agent-profiles --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.

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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