---
name: council
description: Run parallel code reviews with multiple AI agents, then synthesize into one report. Triggers on "review code" or "council review".
---

# Council Code Review Skill

This skill runs the same code review prompt against multiple AI agents in parallel, then synthesizes their findings into a single comprehensive report. It supports **Claude Code**, **Codex CLI**, **OpenCode**, and **Cursor** as agent backends -- and you can mix them freely.

## When to Use

Activate this skill when the user asks to:
- "Review my code"
- "Run a code review"
- "Review the staged changes"
- "Do a council review"
- "Get multiple perspectives on this code"

## CRITICAL: Target Directory

**You must pass the USER'S PROJECT DIRECTORY as an argument to the script.**

The user's project directory is where they started their agent session - NOT this skill's directory. Look for the git repository path in the conversation context (e.g., `/Users/.../git/jupyter_server`).

## Workflow

### Step 1: Identify the Target Repository

Determine the user's project directory from the conversation context. This is typically shown at the start of the session or can be found by checking where `AGENTS.md`, `CLAUDE.md`, or similar agent guidance is located. It is NOT `/Users/.../skills/council/`.

### Step 2: Run Parallel Reviews

Run this skill's review script and **pass the user's project directory as an argument**:

```bash
<skill-root>/scripts/run-reviews.sh /path/to/users/project
```

Resolve `<skill-root>` to the directory containing this `SKILL.md`.

For example, if the user is working in `/Users/you/git/jupyter_server`:
```bash
<skill-root>/scripts/run-reviews.sh /Users/you/git/jupyter_server
```

**IMPORTANT**: Always pass the full path to the user's project as the first argument.

The script reads `config.yaml` from the skill directory to determine which agents to run. Each agent entry specifies its own **backend** and **model**, so you can mix and match freely across all four supported backends.

This will:
- Run all configured agents in parallel, each via its own backend
- Save individual JSON results to `<project>/.reviews/`
- Take 1-3 minutes depending on code size

### Step 3: Synthesize Results

After the script completes, read all JSON files from `<project>/.reviews/` (in the user's project directory) and synthesize them into a combined report.

**Synthesis Rules:**
1. Do NOT mention which agent found which issue
2. Deduplicate similar issues (same file + same line + same problem = one entry)
3. If reviewers disagree on severity, use the higher severity
4. Preserve unique findings from each reviewer
5. Present findings as if from a single thorough review

**Output Format:**

Write the combined report to `<project>/.reviews/COMBINED_REVIEW.md` using this structure:

```markdown
# Code Review Report

**Repository:** [repo name from user's directory]
**Date:** [today's date]

---

## Summary

[1-2 paragraph summary]

**Consensus:** [X of Y reviewers recommended changes / approved]

---

## Critical Issues (Require Action)

### 1. [Issue Title]
**Severity:** 🔴 HIGH
**File:** `path/to/file` (line X)

[Description]

**Recommendation:** [How to fix]

---

## Medium Issues (Should Address)

[Same format, 🟠 MEDIUM]

## Low Issues (Consider Addressing)

[Same format, 🟡 LOW]

## Suggested Improvements

[Numbered list]

---

## Verdict

**[🔴 REQUEST CHANGES / 🟢 APPROVE]**

[Priority action items table]
```

### Step 4: Report to User

After writing the combined report, summarize the key findings:
- Total issues found (by severity)
- Top 3 priority items to address
- Overall verdict

## Configuration

All configuration lives in `<skill-root>/config.yaml`:

```yaml
# Each agent specifies its own backend and model.
# Mix and match all four backends freely.
agents:
  - backend: claude-code
    model: sonnet

  - backend: codex
    model: gpt-5.3-codex

  - backend: opencode
    model: google/gemini-3.1-pro
```

### Backends

Each agent entry requires a `backend` and a `model`:

| Backend | CLI command | `model` format | Requires |
|---------|-----------|---------------|----------|
| `claude-code` | `claude -p` | Alias (`sonnet`, `opus`) or full name (`claude-opus-4-7`) | [Claude Code](https://docs.anthropic.com/en/docs/claude-code) + Anthropic account |
| `codex` | `codex exec` | Model name (e.g. `gpt-5.3-codex`) | [Codex CLI](https://github.com/openai/codex) + ChatGPT plan or API key |
| `opencode` | `opencode run` | `provider/model` (e.g. `anthropic/claude-opus-4-7`) | [OpenCode CLI](https://opencode.ai) + provider API keys |
| `cursor` | `cursor-agent` | Model name (e.g. `gemini-3.1-pro`) | [Cursor CLI](https://cursor.com/cli) + subscription |

### Discovering available models

- **Claude Code**: `claude --model` (aliases: `sonnet`, `opus`, `haiku`)
- **Codex**: `/model` inside `codex` TUI, or see [Codex models docs](https://developers.openai.com/codex/models)
- **OpenCode**: `opencode models`
- **Cursor**: `cursor-agent --list-models`

### Other customization

- **Review focus**: Edit `<skill-root>/prompts/review-prompt.md`
- **Thinking depth**: Add "think hard" or "ultrathink" to the prompt

## Files

```
council/
├── SKILL.md              # This file
├── config.yaml           # Backend and model configuration
├── scripts/
│   └── run-reviews.sh    # Parallel review runner
└── prompts/
    └── review-prompt.md  # Review prompt template

# Output is saved to the user's project:
<project>/.reviews/
├── review_*.json         # Individual agent outputs
└── COMBINED_REVIEW.md    # Synthesized report
```