Aif Review

Code Review Assistant

Perform thorough code reviews focusing on correctness, security, performance, and maintainability.

Step 0: Load Config

FIRST: Read .ai-factory/config.yaml if it exists to resolve:

• Paths: paths.description, paths.architecture, paths.rules_file, paths.roadmap, and paths.rules
• Language: language.ui for review summary language
• Git: git.base_branch for branch comparison guidance

If config.yaml doesn't exist, use defaults:

• Paths: .ai-factory/ for all artifacts
• Language: en (English)
• Git: base_branch: main

Behavior

Without Arguments (Review Staged Changes)

1. Run git diff --cached to get staged changes
2. If nothing staged, run git diff for unstaged changes
3. Analyze each file's changes

With PR Number/URL

1. Use gh pr view <number> --json to get PR details
2. Use gh pr diff <number> to get the diff
3. Review all changes in the PR

With Git Ref (Commits Mode)

Argument routing chain:

1. Empty → staged review (see above)
2. Digits or #N → PR mode (see above)
3. Everything else → validate via git rev-parse --verify → commits mode or ask user

Validation:

git rev-parse --verify <argument> 2>/dev/null

• Valid ref → enter commits mode (steps below)

• Invalid ref → do NOT fall back to staged review silently. Ask the user to clarify:

  AskUserQuestion: `<argument>` is not a valid git ref. What did you mean?
  
  Options:
  1. Review staged changes instead
  2. Cancel
  

  Based on choice:

  • "Review staged changes" → run staged review (default mode)
  • "Cancel" → inform the user that review was cancelled → STOP
  • "Other" → user provides corrected ref → re-validate via rev-parse

Edge case: a branch with a purely numeric name (e.g. 123) will be interpreted as a PR number — acceptable compromise.

Steps:

1. Get commit list between the ref and HEAD:

   git log --oneline --reverse <ref>..HEAD
   

   If no commits found (HEAD is at or behind <ref>), inform the user and stop.

2. Check commit count: If more than 20 commits, ask the user before proceeding:

   AskUserQuestion: Found <N> commits to review. Reviewing all of them will be slow and consume significant context. How to proceed?
   
   Options:
   1. Review all <N> commits
   2. Review only the last 20
   3. Cancel
   

   Based on choice:

   • "Review all" → continue with the full commit list
   • "Review only the last 20" → truncate the list to the 20 most recent commits (keep chronological order)
   • "Cancel" → inform the user that review was cancelled → STOP

3. Review each commit:

   git show <commit-hash> --stat
   git show <commit-hash>
   

   For each commit check:

   • Does the commit message match the actual changes?
   • Are changes atomic (single logical unit per commit)?
   • Are there any issues introduced in this specific commit?

4. Provide combined summary with per-commit notes

Context Gates (Read-Only)

Before finalizing review findings, run read-only context gates:

• Check the resolved architecture artifact (if present) for boundary/dependency alignment issues.
• Check the resolved RULES.md artifact (if present) for explicit convention violations.
• Check the resolved roadmap artifact (if present) for milestone alignment and mention missing linkage for likely feat/fix/perf work.

Human gate result severity:

• WARN for non-blocking inconsistencies or missing optional files.
• ERROR only for explicit blocking criteria requested by the user/review policy.

If the user wants a standalone rules-only pass, suggest /aif-rules-check. Keep human /aif-review gate labels at WARN / ERROR, then append the standard machine-readable gate result with pass|warn|fail status.

Machine-readable gate result:

• Append one final fenced aif-gate-result JSON block after the human-readable review.
• Use "gate": "review".
• Use "status": "pass|warn|fail" where:
  • fail = review findings should block merge, including critical correctness, security, data-loss, performance, or explicit blocking context-gate issues.
  • warn = only non-blocking findings, suggestions, missing optional context, or review uncertainty remain.
  • pass = no material review findings remain.
• Use "blocking": true|false.
• Include merge-blocking review findings only in "blockers": [.
• Include reviewed or implicated paths in "affected_files": [.
• Set "suggested_next": { to /aif-fix, /aif-rules, /aif-architecture, /aif-roadmap, /aif-commit, or null.

/aif-review is read-only for context artifacts by default. Do not modify context files unless user explicitly asks.

Project Context

Read .ai-factory/skill-context/aif-review/SKILL.md — MANDATORY if the file exists.

This file contains project-specific rules accumulated by /aif-evolve from patches, codebase conventions, and tech-stack analysis. These rules are tailored to the current project.

How to apply skill-context rules:

• Treat them as project-level overrides for this skill's general instructions
• When a skill-context rule conflicts with a general rule written in this SKILL.md, the skill-context rule wins (more specific context takes priority — same principle as nested CLAUDE.md files)
• When there is no conflict, apply both: general rules from SKILL.md + project rules from skill-context
• Do NOT ignore skill-context rules even if they seem to contradict this skill's defaults — they exist because the project's experience proved the default insufficient
• CRITICAL: skill-context rules apply to ALL outputs of this skill — including the review summary format and the checklist criteria. If a skill-context rule says "review MUST check X" or "summary MUST include section Y" — you MUST augment the output accordingly. Producing a review that ignores skill-context rules is a bug.

Enforcement: After generating any output artifact, verify it against all skill-context rules. If any rule is violated — fix the output before presenting it to the user.

Review Checklist

Correctness

• Logic errors or bugs
• Edge cases handling
• Null/undefined checks
• Error handling completeness
• Type safety (if applicable)

Security

• SQL injection vulnerabilities
• XSS vulnerabilities
• Command injection
• Sensitive data exposure
• Authentication/authorization issues
• CSRF protection
• Input validation

Performance

• N+1 query problems
• Unnecessary re-renders (React)
• Memory leaks
• Inefficient algorithms
• Missing indexes (database)
• Large payload sizes

Best Practices

• Code duplication
• Dead code
• Magic numbers/strings
• Proper naming conventions
• SOLID principles
• DRY principle

Testing

• Test coverage for new code
• Edge cases tested
• Mocking appropriateness

Output Format

## Code Review Summary

**Files Reviewed:** [count]
**Risk Level:** 🟢 Low / 🟡 Medium / 🔴 High

### Context Gates
[Architecture / Rules / Roadmap gate results with WARN/ERROR labels]

### Critical Issues
[Must be fixed before merge]

### Suggestions
[Nice to have improvements]

### Questions
[Clarifications needed]

### Positive Notes
[Good patterns observed]

Append the final machine-readable result after the markdown summary:

{
  "schema_version": 1,
  "gate": "review",
  "status": "pass",
  "blocking": false,
  "blockers": [],
  "affected_files": [],
  "suggested_next": {
    "command": "/aif-commit",
    "reason": "Review found no blocking issues."
  }
}

Schema reminder: "status": "pass|warn|fail", "blocking": true|false, "blockers": [, "affected_files": [, "suggested_next": {.

Review Style

• Be constructive, not critical
• Explain the "why" behind suggestions
• Provide code examples when helpful
• Acknowledge good code
• Prioritize feedback by importance
• Ask questions instead of making assumptions

Examples

User: /aif-review Review staged changes in current repository.

User: /aif-review 123 Review PR #123 using GitHub CLI.

User: /aif-review https://github.com/org/repo/pull/123 Review PR from URL.

User: /aif-review 2.x Review all commits on the current branch compared to branch 2.x.

User: /aif-review main Review all commits on the current branch compared to main (or to whatever branch is configured as git.base_branch in this repository).

User: /aif-review v1.0.0 Review all commits on the current branch compared to tag v1.0.0.

Integration

If GitHub MCP is configured, can:

• Post review comments directly to PR
• Request changes or approve
• Add labels based on review outcome

Tip: Context is heavy after code review. Consider /clear or /compact before continuing with other tasks.