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
npx -y skills add nota-america/forgecat-agent-profiles --skill gpt-5-4-promptingAssembled 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, andmissing_context_gating. - Review or adversarial review: add
grounding_rules,structured_output_contract, anddig_deeper_nudge. - Research or recommendation tasks: add
research_modeandcitation_rules. - Write-capable tasks: add
action_safetyso Codex stays narrow and avoids unrelated refactors.
How to choose prompt shape:
- Use built-in
revieworadversarial-reviewcommands when the job is reviewing local git changes. Those prompts already carry the review contract. - Use
taskwhen the task is diagnosis, planning, research, or implementation and you need to control the prompt more directly. - Use
task --resume-lastfor 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:
- Define the exact task and scope in
<task>. - Choose the smallest output contract that still makes the answer easy to use.
- Decide whether Codex should keep going by default or stop for missing high-risk details.
- Add verification, grounding, and safety tags only where the task needs them.
- 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
references/
- codex-prompt-antipatterns.md1.5 KB
- codex-prompt-recipes.md4.1 KB
- prompt-blocks.md4.1 KB
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.