
Copilot Cli
- 3 installs
- 318 repo stars
- Updated June 22, 2026
- giuseppe-trisciuoglio/developer-kit-claude-code
This is a copy of copilot-cli by giuseppe-trisciuoglio - installs and ranking accrue to the original listing.
Helps with ai & agent building tasks.
About
copilot-cli is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.
- copilot-cli
- AI & Agent Building
- AI-coding skill
Copilot Cli by the numbers
- 3 all-time installs (skills.sh)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 3 |
|---|---|
| repo stars | ★ 318 |
| Last updated | June 22, 2026 |
| Repository | giuseppe-trisciuoglio/developer-kit-claude-code ↗ |
What it does
Helps with ai & agent building tasks.
Files
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 statusIf 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-toolsonly when multiple tools are clearly needed - Add
--allow-all-pathsonly if task requires broad filesystem access - Add
--allow-all-urlsonly if external URLs are required - Do not use
--yolounless the user explicitly requests full permissions
5) Run delegation command
Base pattern:
copilot -p "<english prompt>" --model <model-name> --allow-all-tools --silentAdd 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 --silent6) Return results clearly
After command execution:
- Return Copilot output concisely
- State model and permission profile used
- If
--shareis 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 \
--silentOutput:
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 \
--shareOutput:
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-toolsOutput:
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
--sharewhen 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--yoloincrease 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.
Copilot CLI Command Reference (Skill Support)
Minimal reference used by the copilot-cli skill.
Core non-interactive patterns
# Programmatic prompt execution
copilot -p "<english prompt>"
# Programmatic prompt with explicit model
copilot -p "<english prompt>" --model <model-name>
# Output only assistant response
copilot -p "<english prompt>" --silentPermission flags
# Single tool (preferred when possible)
copilot -p "<prompt>" --allow-tool 'shell(git)'
# All tools
copilot -p "<prompt>" --allow-all-tools
# All paths
copilot -p "<prompt>" --allow-all-paths
# All URLs
copilot -p "<prompt>" --allow-all-urls
# Full permissions (highest risk)
copilot -p "<prompt>" --yoloSession controls
# Resume a session
copilot --resume <session-id>
# Share session to markdown
copilot -p "<prompt>" --share
# Share session to explicit path
copilot -p "<prompt>" --share ./copilot-session.mdOperational guidance
- Keep prompts in English for consistency and model performance.
- Prefer explicit model selection when reproducibility is important.
- Use least-privilege permission flags; avoid
--yolounless explicitly requested. - Always review output before applying code changes.