Code Review & Quality

SkillAI & models

Five-axis code review for comprehensive quality assessment

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Code Review & Quality skill

What this skill tells your AI

The instructions your AI receives, as published by fdhhhdjd/class-ai-agent in .claude/skills/code-review/SKILL.md and read by ahel’s review.

Philosophy

"Approve a change when it definitely improves overall code health, even if it isn't perfect."

Progress over perfection. Continuous incremental improvement.


Five-Axis Review Framework

Axis 1: Correctness

Questions to ask:

  • Does the implementation match the specification?
  • Are edge cases handled?
  • Are error paths covered?
  • Are there potential runtime issues?
    • Off-by-one errors
    • Race conditions
    • Null/undefined access
    • Resource leaks

Test adequacy:

  • Do tests verify the claimed behavior?
  • Are negative cases tested?
  • Would a bug slip through?

Axis 2: Readability & Simplicity

Questions to ask:

  • Can another engineer understand this without explanation?
  • Are names clear and descriptive?
  • Is control flow straightforward?
  • Is the code organized logically?

Complexity checks:

  • Deep nesting (> 3 levels)?
  • Long functions (> 30 lines)?
  • Clever tricks that obscure intent?
  • Unnecessary abstractions?

Axis 3: Architecture

Questions to ask:

  • Does this follow existing patterns in the codebase?
  • Are module boundaries respected?
  • Is there code duplication that should be extracted?
  • Is the abstraction level appropriate?
  • Do dependencies flow in the right direction?

Over-engineering checks:

  • Is this simpler than it needs to be?
  • Are there abstractions "for future use"?
  • Would a simpler approach work?

Axis 4: Security

Input validation:

  • Is user input validated and sanitized?
  • Are queries parameterized?
  • Is output properly encoded?

Authentication & Authorization:

  • Are auth checks in place?
  • Is ownership verified for resources?
  • Are permissions enforced?

Secrets management:

  • No hardcoded secrets?
  • Sensitive data excluded from logs?
  • External data treated as untrusted?

Axis 5: Performance

Common issues:

  • N+1 query patterns?
  • Unbounded operations (loops, queries)?
  • Missing pagination?
  • Unnecessary re-renders (React)?
  • Objects created in hot paths?
  • Missing indexes for queries?

Async handling:

  • Are async operations properly awaited?
  • Could operations be parallelized?

Change Sizing Guidelines

SizeLinesGuidance
Ideal~100Easy to review thoroughly
Acceptable~300Requires focused review
Too Large1000+Split into smaller PRs

Each PR should be one logical change, not an entire feature.


Comment Severity Labels

Use prefixes to clarify intent:

LabelMeaningAction Required
(none)Required changeMust fix before merge
Critical:Merge blockerMust fix before merge
Nit:Minor/styleOptional, author's choice
Optional:SuggestionConsider, not required
FYI:InformationalNo action needed

Examples:

Critical: This allows SQL injection via the `name` parameter.

Nit: Consider renaming `data` to `userData` for clarity.

Optional: You could use `Array.from()` here instead of spread.

FYI: We have a shared utility for this in `src/utils/format.ts`.

Review Process

Step 1: Understand Context

  • What is this PR trying to achieve?
  • Is there a linked issue or spec?
  • What's the scope of changes?

Step 2: Review Tests First

Tests reveal:

  • What behavior is expected
  • What edge cases are considered
  • Whether coverage is adequate

Step 3: Examine Implementation

Walk through changes with the 5 axes in mind.

Step 4: Categorize Findings

  • Must fix — Correctness, security, critical bugs
  • Should fix — Readability, architecture concerns
  • Consider — Suggestions, style preferences

Step 5: Provide Actionable Feedback

❌ "This is confusing"

✅ "This nested conditional is hard to follow. Consider extracting
    the inner logic to a named function like `isEligibleForDiscount()`"

Review Output Format

## Review: [PR Title]

### Summary
[1-2 sentences on overall assessment]

### Critical Issues
- **[file:line]** [Issue description]

### Important
- **[file:line]** [Issue description]

### Suggestions
- **[file:line]** [Suggestion]

### Verdict
- [ ] Approve
- [ ] Request changes
- [ ] Needs discussion

Rules

  • Don't accept "I'll clean it up later" — It won't happen
  • Remove dead code — Don't comment it out
  • Review within 1 business day — Faster is better
  • Be kind, not nice — Honest feedback helps everyone
  • One approval minimum — Before any merge

Signals

GitHub stars
264
Forks
166
Last commit
Apr 2026
Advanced
Catalog kind
skill
Gateway key
code-review-quality-fdhhhdjd
Source
github.com/fdhhhdjd/class-ai-agent