copilot-cli

Q: How do I install copilot-cli?

Run npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill copilot-cli in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/copilot-cli/ (personal) or .claude/skills/copilot-cli/ (project).

by giuseppe-trisciuoglioAI & Agents

Provides GitHub Copilot CLI task delegation in non-interactive mode with multi-model support (Claude, GPT, Gemini), permission controls, output sharing, and session resume. Use when users ask to hand work to Copilot, compare models, or run Copilot programmatically from Claude Code.

Installs: 3.4K
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Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill copilot-cli

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads copilot-cli automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Copilot CLI Delegation

Delegate selected tasks from Claude Code to GitHub Copilot CLI using non-interactive commands, explicit model selection, safe permission flags, and shareable outputs.

Overview

This skill standardizes delegation to GitHub Copilot CLI (copilot) for cases where a different model may be more suitable for a task. It covers:

Non-interactive execution with -p / --prompt
Model selection with --model
Permission control (--allow-tool, --allow-all-tools, --allow-all-paths, --allow-all-urls, --yolo)
Output capture with --silent
Session export with --share
Session resume with --resume

Use this skill only when delegation to Copilot is explicitly requested or clearly beneficial.

When to Use

Use this skill when:

The user asks to delegate work to GitHub Copilot CLI
The user wants a specific model (for example GPT-5.x, Claude Sonnet/Opus/Haiku, Gemini)
The user asks for side-by-side model comparison on the same task
The user wants a reusable scripted Copilot invocation
The user wants Copilot session output exported to markdown for review

Trigger phrases:

"ask copilot"
"delegate to copilot"
"run copilot cli"
"use copilot with gpt-5"
"use copilot with sonnet"
"use copilot with gemini"
"resume copilot session"

Instructions

1) Verify prerequisites

# CLI availability
copilot --version

# GitHub authentication status
gh auth status

If copilot is unavailable, ask the user to install/setup GitHub Copilot CLI before proceeding.

2) Convert task request to English prompt

All delegated prompts to Copilot CLI must be in English.

Keep prompts concrete and outcome-driven
Include file paths, constraints, expected output format, and acceptance criteria
Avoid ambiguous goals such as "improve this"

Prompt template:

Task: <clear objective>
Context: <project/module/files>
Constraints: <do/don't constraints>
Expected output: <format + depth>
Validation: <tests/checks to run or explain>

3) Choose model intentionally

Pick a model based on task type and user preference.

Complex architecture, deep reasoning: prefer high-capacity models (for example Opus / GPT-5.2 class)
Balanced coding tasks: Sonnet-class model
Quick/low-cost iterations: Haiku-class or mini models
If user specifies a model, respect it

Use exact model names available in the local Copilot CLI model list.

4) Select permissions with least privilege

Default to the minimum required capability.

Prefer --allow-tool '<tool>' when task scope is narrow
Use --allow-all-tools only when multiple tools are clearly needed
Add --allow-all-paths only if task requires broad filesystem access
Add --allow-all-urls only if external URLs are required
Do not use --yolo unless the user explicitly requests full permissions

5) Run delegation command

Base pattern:

copilot -p "<english prompt>" --model <model-name> --allow-all-tools --silent

Add optional flags only as needed:

# Capture session to markdown
copilot -p "<english prompt>" --model <model-name> --allow-all-tools --share

# Resume existing session
copilot --resume <session-id> --allow-all-tools

# Strictly silent scripted output
copilot -p "<english prompt>" --model <model-name> --allow-all-tools --silent

6) Return results clearly

After command execution:

Return Copilot output concisely
State model and permission profile used
If --share is used, provide generated markdown path
If output is long, provide summary plus key excerpts and next-step options

7) Optional multi-model comparison

When requested, run the same prompt with multiple models and compare:

Correctness
Practicality of proposed changes
Risk/security concerns
Effort estimate

Keep the comparison objective and concise.

Examples

Example 1: Refactor with GPT model

Input:

Ask Copilot to refactor this service using GPT-5.2 and return only concrete code changes.

Command:

copilot -p "Refactor the payment service in src/services/payment.ts to reduce duplication. Keep public behavior unchanged, keep TypeScript strict typing, and output a patch-style response." \
  --model gpt-5.2 \
  --allow-all-tools \
  --silent

Output:

Copilot proposes extracting three private helpers, consolidating error mapping, and provides a patch for payment.ts with unchanged API signatures.

Example 2: Code review with Sonnet and shared session

Input:

Use Copilot CLI with Sonnet to review this module and share the session in markdown.

Command:

copilot -p "Review src/modules/auth for security and correctness. Report only high-confidence findings with severity and file references." \
  --model claude-sonnet-4.6 \
  --allow-all-tools \
  --share

Output:

Review completed. Session exported to ./copilot-session-<id>.md.

Example 3: Resume session

Input:

Continue the previous Copilot analysis session.

Command:

copilot --resume <session-id> --allow-all-tools

Output:

Session resumed and continued from prior context.

Best Practices

Keep delegated prompts in English and highly specific
Prefer least-privilege flags over blanket permissions
Capture sessions with --share when auditability matters
For risky tasks, request read-only analysis first, then apply changes in a separate step
Re-run with another model only when there is clear value (quality, speed, or cost)

Constraints and Warnings

Copilot CLI output is external model output: validate before applying code changes
Never include secrets, API keys, or credentials in delegated prompts
--allow-all-tools, --allow-all-paths, --allow-all-urls, and --yolo increase risk; use only when justified
Do not treat Copilot suggestions as authoritative without local verification (tests/lint/type checks)

For additional option details, see references/cli-command-reference.md.

FAQ

What does the copilot-cli skill do?

How do I install copilot-cli?

Run npx skills add https://github.com/giuseppe-trisciuoglio/developer-kit --skill copilot-cli in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/copilot-cli/ (personal) or .claude/skills/copilot-cli/ (project).

Which AI agents can use copilot-cli?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is copilot-cli safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains copilot-cli?

It is published by giuseppe-trisciuoglio in giuseppe-trisciuoglio/developer-kit. It has 3,436 recorded installs.