gpt-5-4-prompting

gpt-5-4-prompting is a skill for Claude Code from mvpasarel/gh-copilot-plugin-cc. It costs 40 tokens per session (774 once invoked), scanned A, a copy of gpt-5-4-prompting, Apache-2.0.

Internal guidance for writing prompts for Copilot and GPT-5.4 during coding, code review, diagnosis, and research tasks.

In plain words
What is it for?
Use it when a Copilot or GPT-5.4 workflow needs a compact, structured prompt.
Why use it?
It gives these requests a clear task, expected output, constraints, and verification requirements.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter. Also seen: mentions Claude Code.

Part of the copilot plugin — 3 skills, 12 commands, 1 agent, 3 hooks shipped together

Good fit Use it when a Copilot or GPT-5.4 workflow needs a compact, structured prompt.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/mvpasarel/gh-copilot-plugin-cc/gpt-5-4-prompting
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add mvpasarel/gh-copilot-plugin-cc --skill gpt-5-4-prompting
Clone the repo
git clone --depth 1 https://github.com/mvpasarel/gh-copilot-plugin-cc

Made for: Claude Code.

Or install copilot, the plugin that ships this one along with the rest of its 3 skills, 12 commands, 1 agent, 3 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for gpt-5-4-prompting

README.md
[![agentmods](https://agentmods.dev/badge/skills/mvpasarel/gh-copilot-plugin-cc/gpt-5-4-prompting/github.svg)](https://agentmods.dev/skills/mvpasarel/gh-copilot-plugin-cc/gpt-5-4-prompting)
Your own site
<a href="https://agentmods.dev/skills/mvpasarel/gh-copilot-plugin-cc/gpt-5-4-prompting"><img src="https://agentmods.dev/badge/skills/mvpasarel/gh-copilot-plugin-cc/gpt-5-4-prompting/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for gpt-5-4-prompting

Your own site · 80×15
<a href="https://agentmods.dev/skills/mvpasarel/gh-copilot-plugin-cc/gpt-5-4-prompting"><img src="https://agentmods.dev/badge/skills/mvpasarel/gh-copilot-plugin-cc/gpt-5-4-prompting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 774 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 83% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.00774
Opus 5 $0.00020 $0.00387
Sonnet 5 $0.00008 $0.00155
Haiku 4.5 $0.00004 $0.00077

Measured 11d ago against content hash 9261decfdd10, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

gpt-5-4-prompting scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

83% identical to gpt-5-4-prompting — 24 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/copilot/skills/gpt-5-4-prompting/SKILL.md · 55 lines

What it actually says

GPT-5.4 Prompting

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

Prompt Copilot 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 Copilot run. Split unrelated asks into separate runs.
  • Tell Copilot 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 Copilot 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 Copilot 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 Copilot session. 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 Copilot 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 Copilot 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/copilot-prompt-recipes.md. Common failure modes to avoid live in references/copilot-prompt-antipatterns.md.

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 55 lines · 40 tokens per session scan A 9261decfdd10

Subscribe to this mod's changes

gpt-5-4-prompting is a skill published in the GitHub repository mvpasarel/gh-copilot-plugin-cc (7 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 40 tokens to every session and 774 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 83% identical to gpt-5-4-prompting, differing in 24 lines, and is treated as a copy.

Related

Other skills, from other repositories

llm-app-patterns

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

davila7/claude-code-templates · 54 tokens

prompt-optimization

Improve a prompt on the evaluations workbench through a measured loop. Score the baseline first, then duplicate the target column, form a hypothesis from failing rows, edit the copy's prompt draft, run, compare pass rate and cost, and repeat until the numbers hold. Use when the user asks to optimize or improve a…

langwatch/langwatch · 105 tokens

enhance-prompt

Transforms vague UI ideas into polished, Stitch-optimized prompts. Enhances specificity, adds UI/UX keywords, injects design system context, and structures output for better generation results.

google-labs-code/stitch-skills · 41 tokens

prompt-engineer

Writes, refactors, and evaluates prompts for LLMs — generating optimized prompt templates, structured output schemas, evaluation rubrics, and test suites. Use when designing prompts for new LLM applications, refactoring existing prompts for better accuracy or token efficiency, implementing chain-of-thought or few-shot…

Jeffallan/claude-skills · 93 tokens

seedance-vocab-en

This skill should be used when an English Seedance 2.0 prompt needs clearer production wording, less generic prose, or precise vocabulary for camera, lighting, motion, VFX, audio, and constraints. Route blocked prompts through seedance-filter for context and boundary review.

Emily2040/seedance-2.0 · 61 tokens

ideogram4

Prompting patterns for Ideogram 4 text-to-image — best-in-class in-image text rendering and exact color/layout control via structured JSON captions. Use when generating images that need legible on-image text (title cards, thumbnails, logos, signage, CTAs), precise brand colors, or controlled spatial layout. Triggers…

digitalsamba/claude-code-video-toolkit · 99 tokens