copilot-prompting

copilot-prompting is a skill for Claude Code from wagnersza/copilot-plugin-cc. It costs 53 tokens per session (849 once invoked), scanned A, a copy of gpt-5-4-prompting, Apache-2.0.

Guidance for writing clear instructions to Copilot, an AI coding assistant, for coding, review, diagnosis, and research tasks.

In plain words
What is it for?
Use it when preparing prompts for Copilot to change code, investigate a problem, review work, or research an answer.
Why use it?
It helps avoid vague requests and unsupported guesses by defining the task, expected result, constraints, and checks clearly.

Skill for Claude Code

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

Part of the copilot plugin — 3 skills, 7 commands, 1 agent, 3 hooks shipped together

Good fit Use it when preparing prompts for Copilot to change code, investigate a problem, review work, or research an answer.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/wagnersza/copilot-plugin-cc/copilot-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 wagnersza/copilot-plugin-cc --skill copilot-prompting
Clone the repo
git clone --depth 1 https://github.com/wagnersza/copilot-plugin-cc

Made for: Claude Code.

Or install copilot, the plugin that ships this one along with the rest of its 3 skills, 7 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 copilot-prompting

README.md
[![agentmods](https://agentmods.dev/badge/skills/wagnersza/copilot-plugin-cc/copilot-prompting.svg)](https://agentmods.dev/skills/wagnersza/copilot-plugin-cc/copilot-prompting)
Your own site
<a href="https://agentmods.dev/skills/wagnersza/copilot-plugin-cc/copilot-prompting"><img src="https://agentmods.dev/badge/skills/wagnersza/copilot-plugin-cc/copilot-prompting.svg" alt="Measured on agentmods" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 849 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 $0.00053 $0.00849
Opus 5 $0.00026 $0.00425
Sonnet 5 $0.00011 $0.00170
Haiku 4.5 $0.00005 $0.00085

Measured 8d ago against content hash 24969c72f9d6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

copilot-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 8d 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 — 33 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/copilot-prompting/SKILL.md · 60 lines

What it actually says

Copilot Prompting

Use this skill when copilot:copilot-rescue needs to ask Copilot or another model-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 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 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.

Model selection notes:

  • GPT-5.4: best for complex multi-step coding, deep diagnosis, and adversarial review.
  • GPT-5.3-Codex: preferred for focused implementation, targeted fixes, and code generation.
  • Gemini 3.1 Pro: use for research, recommendation, and tasks benefiting from broad context.

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. 8d ago First seen · 60 lines · 53 tokens per session scan A 24969c72f9d6

Subscribe to this mod's changes

copilot-prompting is a skill published in the GitHub repository wagnersza/copilot-plugin-cc (45 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 53 tokens to every session and 849 once invoked, about $0.0003 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 33 lines, and is treated as a copy.

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