Use GitHub Copilot models from inside Claude Code — cross-model code reviews, multi-model council reviews, and task delegation.
This plugin lets Claude Code users tap into Copilot's model lineup (GPT-5.4, GPT-5.3-Codex, Claude Opus 4.6, etc.) without leaving their workflow. The headline feature is council reviews: the same diff reviewed by multiple models in parallel, with Claude synthesizing the results.
| Command | What it does |
|---|---|
/copilot:review |
Code review using any Copilot model (default GPT-5.4) |
/copilot:adversarial-review |
Challenge review — questions design, architecture, and assumptions |
/copilot:council |
Multi-model council review — parallel reviews from 3 models, synthesized by Claude |
/copilot:delegate |
Hand a task to Copilot (bug investigation, fixes, research) |
/copilot:status |
Check running and recent jobs |
/copilot:result |
Get the output of a completed job |
/copilot:cancel |
Cancel an active background job |
/copilot:setup |
Check installation, auth, and settings |
The unique feature. /copilot:council sends your diff to multiple models simultaneously and synthesizes the results:
/copilot:council
Default models: GPT-5.4, Claude Opus 4.6, GPT-5.3-Codex (configurable).
The synthesis identifies:
- Agreements — issues flagged by multiple models (high confidence)
- Disagreements — conflicting assessments (needs human judgment)
- Unique catches — issues only one model spotted (edge case signals)
- Overall assessment — combined verdict on code quality
Custom model selection:
/copilot:council --models gpt-5.4,gpt-5.4-mini,gpt-5.3-codex
/copilot:adversarial-review is not a stricter bug hunt — it's a design challenge. Instead of finding implementation defects, it questions whether the approach itself is right:
/copilot:adversarial-review
Focus on a specific concern:
/copilot:adversarial-review is this abstraction worth the complexity?
The review covers:
- Design choices — right abstraction? right layer?
- Architecture tradeoffs — what does this sacrifice? what breaks if requirements change?
- Assumptions — what is the code assuming? are those assumptions safe?
- Missing alternatives — was a simpler approach considered?
- Failure modes — what happens when this fails at 3am?
Optionally block commits that have critical issues. Enable in .claude/copilot.local.md:
- review-gate: onWhen enabled, every git commit runs a fast Copilot review first. It only blocks for critical issues:
- Security vulnerabilities (hardcoded secrets, injection, auth bypass)
- Data loss risks (destructive operations without safeguards)
- Obvious production-crashing bugs
Style issues, missing tests, and subjective preferences are always allowed through. The gate uses gpt-5.4-mini by default for speed (configurable via review-gate-model).
The gate fails open — if Copilot is unavailable, times out, or errors, the commit proceeds normally.
- GitHub Copilot subscription — usage counts toward your Copilot limits. Learn more.
- Copilot CLI installed — via npm, VS Code extension, or manual install.
- Node.js 18+
Add the marketplace and install:
/plugin marketplace add mongo-ai/copilot-claude-code-plugin
/plugin install copilotReload plugins:
/reload-pluginsThen check everything is working:
/copilot:setupIf Copilot CLI isn't installed yet:
npm install -g @github/copilot-cliIf Copilot isn't authenticated:
!copilot loginReview your working tree changes:
/copilot:review
Review against a base branch:
/copilot:review --base main
Use a specific model:
/copilot:review --model gpt-5.3-codex
Run in the background:
/copilot:review --background
/copilot:status
/copilot:result
Hand off work to Copilot:
/copilot:delegate investigate why the auth middleware is returning 403 for valid tokens
Use a specific model:
/copilot:delegate --model gpt-5.4 refactor the database connection pool to use async initialization
Any model available through the Copilot CLI can be used:
| Model | Best for |
|---|---|
gpt-5.4 |
Complex reasoning, thorough reviews (default for review) |
gpt-5.3-codex |
Code-specialized tasks (default for delegate) |
claude-opus-4.6 |
Nuanced analysis, long context |
gpt-5.4-mini |
Quick, low-cost tasks |
Create .claude/copilot.local.md in your repo to customize defaults:
- default-model: gpt-5.4
- default-effort: high
- council-models: gpt-5.4, claude-opus-4.6, gpt-5.3-codex
- council-effort: high
- copilot-binary: auto
- review-gate: off
- review-gate-model: gpt-5.4-mini| Setting | Default | Description |
|---|---|---|
default-model |
gpt-5.4 |
Model for /copilot:review |
default-effort |
high |
Reasoning effort level |
council-models |
gpt-5.4, claude-opus-4.6, gpt-5.3-codex |
Models for council review |
council-effort |
high |
Effort level for council reviews |
copilot-binary |
auto |
Path to Copilot CLI binary, or auto to detect |
review-gate |
off |
Set to on to gate commits on Copilot review |
review-gate-model |
gpt-5.4-mini |
Model for review gate (fast + cheap) |
The plugin spawns the Copilot CLI directly — no SDK dependency, no extra npm install. It finds the binary automatically (PATH, VS Code extension paths, or manual config).
For council reviews, all models run in parallel via Promise.allSettled. If rate limiting is detected, it falls back to sequential execution with delays.
Background jobs are tracked as JSON files in .copilot-jobs/ (gitignored) with PID-based lifecycle management.
commands/ Slash command definitions (8 commands)
council.md Multi-model council review (unique feature)
adversarial-review.md Challenge review — design & architecture
review.md Single-model code review
delegate.md Task delegation
setup.md Installation check
status.md Job status
result.md Job output
cancel.md Job cancellation
agents/
copilot-delegate.md Subagent for task delegation
hooks/
hooks.json SessionStart + review gate hooks
scripts/
copilot-companion.mjs Main entry point
review-gate-hook.mjs PreToolUse hook for commit gating
lib/
copilot.mjs CLI binary discovery + process spawning
git.mjs Diff collection + review size estimation
state.mjs Background job tracking (JSON file-based)
settings.mjs Configuration reader (.claude/copilot.local.md)
tests/ 83 tests across 4 modules
Apache 2.0 — see LICENSE.
Architecture inspired by openai/codex-plugin-cc.