Philosophy-aware pull request reviews that go beyond syntax and style to check alignment with amplihack's core development principles. This skill reviews PRs not just for correctness, but for ruthless simplicity, modular architecture, and zero-BS implementation.
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node --versionpr-review-assistantExecute the skills CLI command in your project's root directory to begin installation:
Fetches pr-review-assistant from rysweet/amplihack and configures it for Cursor.
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Confirm successful installation by checking the skill directory location:
Restart Cursor to activate pr-review-assistant. Access via /pr-review-assistant in your agent's command palette.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Philosophy-aware pull request reviews that go beyond syntax and style to check alignment with amplihack's core development principles. This skill reviews PRs not just for correctness, but for ruthless simplicity, modular architecture, and zero-BS implementation.
Every line of code must justify its existence. We ask:
Code should be organized as self-contained modules with clear connections:
No shortcuts, stubs, or technical debt:
Start by understanding what the PR changes:
Review each change against amplihack principles:
Look for common over-engineering patterns:
If new modules or module changes:
Adequate testing is crucial:
When suggesting changes:
PR: Add user permission checking to API
Code Changed:
class PermissionValidator:
def __init__(self):
self.cache = {}
def validate(self, user, resource):
if user in self.cache:
return self.cache[user]
result = self._complex_validation(user, resource)
self.cache[user] = result
return result
def _complex_validation(self, user, resource):
# Complex business logic...
pass
Review Comment:
FILE: permissions.py (lines 10-25)
This over-engineers the permission checking with caching that may not be needed.
The caching layer adds complexity without proven benefit:
1. Cache can become stale if user permissions change
2. Unclear when/if cache should be invalidated
3. In-memory cache doesn't scale across processes
4. Permission checks are usually not in hot paths
SUGGESTION - Start simpler:
```python
def check_permission(user, resource):
"""Check if user can access resource."""
# Direct implementation
return user.has_access_to(resource)
If caching is needed later, add it when profiling shows it helps.
This aligns with ruthless simplicity: don't add complexity until proven necessary.
### Example 2: Identifying Lack of Regeneration Documentation
**PR**: Add new authentication module
**Code Changed**: New file `~/.amplihack/.claude/tools/auth/auth.py`
**Review Comment**:
FILE: .claude/tools/auth/ (new module)
Good: Module has clear responsibilities (JWT validation, token refresh). Issue: Missing specification documentation for module regeneration.
Brick Philosophy Requirement: Modules should be regeneratable from spec.
ACTION NEEDED:
This enables future rebuilding if requirements change.
See .claude/skills/pr-review-assistant/ for specification template.
### Example 3: Identifying Zero-BS Issues
**PR**: Add data processing pipeline
**Code Changed**:
```python
def process_data(data):
"""Process data through pipeline."""
# TODO: Add error handling
result = validate(data)
if not result:
return None # swallowed error
# TODO: Implement caching
return transform(result)
Review Comment:
FILE: pipeline.py (lines 5-15)
Zero-BS Issues Found:
1. LINE 6: TODO comments - implement or remove
- "Add error handling" - Either add it now or create issue
- "Implement caching" - Not needed yet; add if profiling shows benefit
2. LINE 10: Swallowed error
- validate() likely raised exception, but returns None
- Make error explicit: raise ValueError("Invalid data")
- Or catch and re-raise with context
3. LINE 8: Silent failures
- If None is returned, caller doesn't know why
- Either raise exception or return Result type
SUGGESTION:
```python
def process_data(data):
"""Process data through pipeline.
Raises:
ValueError: If data validation fails
"""
result = validate(data) # Raises if invalid
return transform(result)
All code is production-ready, no TODOs.
### Example 4: Identifying Missing Tests
**PR**: Add user role management
**Code Changed**: New class `RoleManager` in user module
**Review Comment**:
FILE: user.py (lines 50-100)
New functionality added without adequate tests.
ISSUE: RoleManager public interface not tested
EDGE CASES MISSING:
CONTRACT VERIFICATION:
ADD: tests/test_role_manager.py with 85%+ coverage
### Example 5: Recognizing Good Design
**PR**: Add simplified config loader
**Code Changed**:
```python
def load_config(path):
"""Load YAML config from file.
Args:
path: Path to config file
Returns:
dict: Parsed config
Raises:
FileNotFoundError: If file doesn't exist
ValueError: If YAML is invalid
"""
with open(path) as f:
try:
return yaml.safe_load(f)
except yaml.YAMLError as e:
raise ValueError(f"Invalid YAML: {e}") from e
Review Comment:
EXCELLENT - This is exactly the simplicity we want:
✅ Single responsibility: Load and parse YAML
✅ Clear error handling: Explicit exceptions with context
✅ No TODOs or stubs: Production ready
✅ Complete documentation: Clear args, returns, exceptions
✅ No over-engineering: Direct implementation
✅ Testable: Clear behavior to verify
This is a model example of ruthless simplicity.
When commenting on PRs, use this structure:
**FILE**: path/to/file.py (lines X-Y)
**ISSUE**: [Principle violated - Simplicity/Modularity/Zero-BS/Tests/Docs]
**WHAT**: [Describe what's in the code]
**WHY IT'S PROBLEMATIC**: [How it violates amplihack principles]
**SUGGESTION**: [Concrete code example or approach]
**REFERENCE**: [Link to relevant philosophy, principle, or example]
The skill can post review comments to GitHub PRs using:
gh pr comment <PR-NUMBERMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
I recommend pr-review-assistant for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
pr-review-assistant reduced setup friction for our internal harness; good balance of opinion and flexibility.
pr-review-assistant is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: pr-review-assistant is the kind of skill you can hand to a new teammate without a long onboarding doc.
pr-review-assistant is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added pr-review-assistant from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
pr-review-assistant fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for pr-review-assistant matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: pr-review-assistant is the kind of skill you can hand to a new teammate without a long onboarding doc.
pr-review-assistant is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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