qwen-code/docs/users/features/code-review.md

Code Review

Review code changes for correctness, security, performance, and code quality using /review.

Quick Start

# Review local uncommitted changes
/review

# Review a pull request (by number or URL)
/review 123
/review https://github.com/org/repo/pull/123

# Review and post inline comments on the PR
/review 123 --comment

# Review a specific file
/review src/utils/auth.ts

If there are no uncommitted changes, /review will let you know and stop — no agents are launched.

How It Works

The /review command runs a multi-stage pipeline:

Determine scope (local diff / PR worktree / file)
        |
Load project review rules
        |
Run deterministic analysis (linter, typecheck)         [zero LLM cost]
        |
5 parallel review agents                               [5 LLM calls]
  |-- Agent 1: Correctness & Security
  |-- Agent 2: Code Quality
  |-- Agent 3: Performance & Efficiency
  |-- Agent 4: Undirected Audit
  '-- Agent 5: Build & Test                             [zero LLM cost]
        |
Deduplicate --> Batch verify --> Aggregate              [1 LLM call]
        |
Reverse audit (find coverage gaps)                      [1 LLM call]
        |
Present findings + verdict
        |
Autofix (user-confirmed, optional)
        |
Post PR inline comments (if requested)
        |
Save report + incremental cache
        |
Clean up (remove worktree + temp files)

Review Agents

Agent	Focus
Agent 1: Correctness & Security	Logic errors, null handling, race conditions, injection, XSS, SSRF
Agent 2: Code Quality	Style consistency, naming, duplication, dead code
Agent 3: Performance & Efficiency	N+1 queries, memory leaks, unnecessary re-renders, bundle size
Agent 4: Undirected Audit	Business logic, boundary interactions, hidden coupling
Agent 5: Build & Test	Runs build and test commands, reports failures

All agents run in parallel. All findings are then verified in a single batch verification pass (one agent reviews all findings at once, keeping LLM calls fixed regardless of finding count). After verification, a reverse audit agent reviews the diff with knowledge of all confirmed findings to catch issues that every other agent missed. Any reverse audit findings are also batch-verified before inclusion in the final results.

Deterministic Analysis

Before the LLM agents run, /review automatically runs your project's existing linters and type checkers:

Language	Tools detected
TypeScript/JavaScript	tsc --noEmit, npm run lint, eslint
Python	ruff, mypy, flake8
Rust	cargo clippy
Go	go vet, golangci-lint

Deterministic findings are tagged with [linter] or [typecheck] and skip LLM verification — they are ground truth.

• Errors → Critical severity
• Warnings → Nice to have (terminal only, not posted as PR comments)

If a tool is not installed or times out, it is skipped with an informational note.

Severity Levels

Severity	Meaning	Posted as PR comment?
Critical	Must fix before merging (bugs, security, data loss, build failures)	Yes (high-confidence only)
Suggestion	Recommended improvement	Yes (high-confidence only)
Nice to have	Optional optimization	No (terminal only)

Low-confidence findings appear in a separate "Needs Human Review" section in the terminal and are never posted as PR comments.

Autofix

After presenting findings, /review offers to auto-apply fixes for Critical and Suggestion findings that have clear solutions:

Found 3 issues with auto-fixable suggestions. Apply auto-fixes? (y/n)

• Fixes are applied using the edit tool (targeted replacements, not full-file rewrites)
• Per-file linter checks run after fixes to verify they don't introduce new issues
• For PR reviews, fixes are committed and pushed from the worktree automatically — your working tree stays clean
• Nice to have and low-confidence findings are never auto-fixed
• PR review submission always uses the pre-fix verdict (e.g., "Request changes") since the remote PR hasn't been updated until the autofix push completes

Worktree Isolation

When reviewing a PR, /review creates a temporary git worktree (.qwen/tmp/review-pr-<number>) instead of switching your current branch. This means:

• Your working tree, staged changes, and current branch are never touched
• Dependencies are installed in the worktree (npm ci, etc.) so linting and build/test work
• Build and test commands run in isolation without polluting your local build cache
• If anything goes wrong, your environment is unaffected — just delete the worktree
• The worktree is automatically cleaned up after the review completes
• If a review is interrupted (Ctrl+C, crash), the next /review of the same PR automatically cleans up the stale worktree before starting fresh
• Review reports and cache are saved to the main project directory (not the worktree)

PR Inline Comments

Use --comment to post findings directly on the PR:

/review 123 --comment

Or, after running /review 123, type post comments to publish findings without re-running the review.

What gets posted:

• High-confidence Critical and Suggestion findings as inline comments on specific lines
• A review summary with verdict (Approve / Request changes / Comment)
• Model attribution footer (e.g., Reviewed by qwen3-coder via Qwen Code /review)

What stays terminal-only:

• Nice to have findings (including linter warnings)
• Low-confidence findings

Follow-up Actions

After the review, context-aware tips appear as ghost text. Press Tab to accept:

State after review	Tip	What happens
Local review with unfixed findings	fix these issues	LLM interactively fixes each finding
PR review with findings	post comments	Posts PR inline comments (no re-review)
Local review, all clear	commit	Commits your changes

Note: fix these issues is only available for local reviews. For PR reviews, use Autofix (Step 3.5) — the worktree is cleaned up after the review, so post-review interactive fixing is not possible.

Project Review Rules

You can customize review criteria per project. /review reads rules from these files (in order):

1. .qwen/review-rules.md (Qwen Code native)
2. .github/copilot-instructions.md (preferred) or copilot-instructions.md (fallback — only one is loaded, not both)
3. AGENTS.md — ## Code Review section
4. QWEN.md — ## Code Review section

Rules are injected into the LLM review agents (1-4) as additional criteria. For PR reviews, rules are read from the base branch to prevent a malicious PR from injecting bypass rules.

Example .qwen/review-rules.md:

# Review Rules

- All API endpoints must validate authentication
- Database queries must use parameterized statements
- React components must not use inline styles
- Error messages must not expose internal paths

Incremental Review

When reviewing a PR that was previously reviewed, /review only examines changes since the last review:

# First review — full review, cache created
/review 123

# PR updated with new commits — only new changes reviewed
/review 123

Cross-model review

If you switch models (via /model) and re-review the same PR, /review detects the model change and runs a full review instead of skipping:

# Review with model A
/review 123

# Switch model
/model

# Review again — full review with model B (not skipped)
/review 123
# → "Previous review used qwen3-coder. Running full review with gpt-4o for a second opinion."

Cache is stored in .qwen/review-cache/ and tracks both the commit SHA and model ID. Make sure this directory is in your .gitignore (a broader rule like .qwen/* also works). If the cached commit was rebased away, it falls back to a full review.

Review Reports

Every review is saved as a Markdown file in your project's .qwen/reviews/ directory:

.qwen/reviews/2026-04-06-143022-pr-123.md
.qwen/reviews/2026-04-06-150510-local.md

Reports include: timestamp, diff stats, deterministic analysis results, all findings with verification status, and the verdict.

Cross-file Impact Analysis

When code changes modify exported functions, classes, or interfaces, the review agents automatically search for all callers and check compatibility:

• Parameter count/type changes
• Return type changes
• Removed or renamed public methods
• Breaking API changes

For large diffs (>10 modified symbols), analysis prioritizes functions with signature changes.

Token Efficiency

The review pipeline uses a fixed number of LLM calls regardless of how many findings are produced:

Stage	LLM calls	Notes
Deterministic analysis (Step 1.5)	0	Shell commands only
Build & test (Agent 5)	0	Shell commands only
5 review agents (Step 2)	5	Run in parallel
Batch verification (Step 2.5)	1	Single agent verifies all findings at once
Reverse audit (Step 2.6)	1	Finds coverage gaps
Total	7	Fixed, not proportional to finding count

What's NOT Flagged

The review intentionally excludes:

• Pre-existing issues in unchanged code (focus on the diff only)
• Style/formatting/naming that matches your codebase conventions
• Issues a linter or type checker would catch (handled by deterministic analysis)
• Subjective "consider doing X" suggestions without a real problem
• Minor refactoring that doesn't fix a bug or risk
• Missing documentation unless the logic is genuinely confusing
• Issues already discussed in existing PR comments (avoids duplicating human feedback)

Design Philosophy

Silence is better than noise. Every comment should be worth the reader's time.

• If unsure whether something is a problem → don't report it
• Linter/typecheck issues are handled by tools, not LLM guesses
• Same pattern across N files → aggregated into one finding
• PR comments are high-confidence only
• Style/formatting issues matching codebase conventions are excluded