code-review

name	code-review
description	Review code changes with parallel detection agents and smart fixing
user-invocable	true

Language-agnostic code review with dynamic agent planning. Adapts to any language, framework, and project size.

Usage

/code-review                          # Interactive — asks what to review
/code-review --full                   # Review entire codebase
/code-review all                      # Same as --full
/code-review --files src/api tests/   # Review specific paths
/code-review <issue-id>              # Review changes for a beads issue
/code-review --quick                  # Fast mode: lint/build check only

How It Works

SELECT → DISCOVER → SCOPE → PLAN → SCAN (parallel) → AGGREGATE → FIX (if needed) → REPORT

0. Select

If no flags given, asks what to review (diff, full codebase, specific paths, beads issue, or quick check).

1. Discover

Auto-detects languages, frameworks, linters, and build tools by scanning the project.

2. Scope

Determines what to review based on invocation mode:

• No args: uncommitted changes (git diff HEAD)
• --full: entire codebase (prioritizes recently changed files for large projects)
• --files: specific paths
• <issue-id>: changes for a beads issue (MCP show or bd show)

3. Plan

Dynamically decides how many scanner agents (2-8) and what each focuses on, based on:

• Project language(s) and frameworks
• Scope size (lines changed / files to review)
• Available linters and build tools
• Whether CLAUDE.md exists

4. Scan

Launches all planned agents in parallel:

• scanner agents (Sonnet) — each with a focused prompt crafted from the language pattern library
• claude-md-scan (Haiku) — CLAUDE.md compliance, if applicable

5. Aggregate

Merges findings from all agents, deduplicates, filters by confidence (>= 80%).

6. Fix (conditional)

Only if issues found: launches fixer (Opus) with the project's build/lint commands for verification.

• Auto-fixes >= 90% confidence
• Adds TODO comments for 80-89%
• Verifies fixes with project's native tools

7. Report

Clear pass/fail report with categorized findings.

Agents

Agent	Purpose	Model
scanner	Generic scanner, invoked N times with different focus prompts	Sonnet
claude-md-scan	CLAUDE.md compliance check	Haiku
fixer	Apply fixes for high-confidence issues	Opus

Supported Languages

Works with any language. Built-in pattern libraries for:

• Go — error handling, nil deref, goroutine leaks, SQL injection
• Python — bare except, mutable defaults, eval(), import cycles
• TypeScript/JavaScript — empty catch, floating promises, XSS, type coercion
• Rust — unwrap(), unsafe blocks, deadlocks

For unlisted languages, the orchestrator infers patterns from the project structure and CLAUDE.md.

Cost Optimization

Scenario	Agents Used	Cost
Clean code (small diff)	2-3 Sonnet	$
Clean code (large/full)	5-8 Sonnet	$$
Issues found	N Sonnet + 1 Opus	$$$ (only when needed)
Quick mode	0 agents	Free

Confidence Scoring

Score	Action
0-79	Skip
80-89	Flag + TODO comment
90-100	Auto-fix

Integration with Beads

Prefer MCP tools when available, fall back to CLI:

# Get issue context (MCP preferred)
mcp__beads__show(issue_id="<issue-id>")
# CLI fallback: bd show <issue-id> --json

/code-review <issue-id>

# If passed (MCP preferred)
mcp__beads__update(issue_id="<issue-id>", status="reviewed")
# CLI fallback: bd update <issue-id> --status=reviewed

Notes

• All scanner agents run in parallel (single message, multiple Task calls)
• Opus fixer only runs when issues are found
• Scanner prompts are crafted dynamically — no hardcoded language assumptions
• Use --quick for trivial changes (docs, config)
• Use --full for comprehensive codebase review