copilot-cli

# 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 ```bash # 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: ```text 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: ```bash copilot -p "<english prompt>" --model <model-name> --allow-all-tools --silent ``` Add optional flags only as needed: ```bash # 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: ```text Ask Copilot to refactor this service using GPT-5.2 and return only concrete code changes. ``` Command: ```bash 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: ```text 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: ```text Use Copilot CLI with Sonnet to review this module and share the session in markdown. ``` Command: ```bash 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: ```text Review completed. Session exported to ./copilot-session-<id>.md. ``` ### Example 3: Resume session Input: ```text Continue the previous Copilot analysis session. ``` Command: ```bash copilot --resume <session-id> --allow-all-tools ``` Output: ```text 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`.