Dispatch code review subagents with focused context to catch issues before they compound.
Works with
Integrates with subagent-driven development workflows, triggering review after each task or before merging to main
Provides code-reviewer subagent with precise git SHAs, implementation details, and requirements, keeping reviewer focused on work product rather than session history
Categorizes feedback into Critical (fix immediately), Important (fix before proceeding), and Minor (note for later) s
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionrequesting-code-reviewExecute the skills CLI command in your project's root directory to begin installation:
Fetches requesting-code-review from obra/superpowers and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate requesting-code-review. Access via /requesting-code-review in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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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Dispatch superpowers:code-reviewer subagent to catch issues before they cascade. The reviewer gets precisely crafted context for evaluation — never your session's history. This keeps the reviewer focused on the work product, not your thought process, and preserves your own context for continued work.
Core principle: Review early, review often.
Mandatory:
Optional but valuable:
1. Get git SHAs:
BASE_SHA=$(git rev-parse HEAD~1) # or origin/main
HEAD_SHA=$(git rev-parse HEAD)
2. Dispatch code-reviewer subagent:
Use Task tool with superpowers:code-reviewer type, fill template at code-reviewer.md
Placeholders:
{WHAT_WAS_IMPLEMENTED} - What you just built{PLAN_OR_REQUIREMENTS} - What it should do{BASE_SHA} - Starting commit{HEAD_SHA} - Ending commit{DESCRIPTION} - Brief summary3. Act on feedback:
[Just completed Task 2: Add verification function]
You: Let me request code review before proceeding.
BASE_SHA=$(git log --oneline | grep "Task 1" | head -1 | awk '{print $1}')
HEAD_SHA=$(git rev-parse HEAD)
[Dispatch superpowers:code-reviewer subagent]
WHAT_WAS_IMPLEMENTED: Verification and repair functions for conversation index
PLAN_OR_REQUIREMENTS: Task 2 from docs/superpowers/plans/deployment-plan.md
BASE_SHA: a7981ec
HEAD_SHA: 3df7661
DESCRIPTION: Added verifyIndex() and repairIndex() with 4 issue types
[Subagent returns]:
Strengths: Clean architecture, real tests
Issues:
Important: Missing progress indicators
Minor: Magic number (100) for reporting interval
Assessment: Ready to proceed
You: [Fix progress indicators]
[Continue to Task 3]
Subagent-Driven Development:
Executing Plans:
Ad-Hoc Development:
Never:
If reviewer wrong:
See template at: requesting-code-review/code-reviewer.md
Make 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.
asyrafhussin/agent-skills
shadcn/improve
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
I recommend requesting-code-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: requesting-code-review is the kind of skill you can hand to a new teammate without a long onboarding doc.
Solid pick for teams standardizing on skills: requesting-code-review is focused, and the summary matches what you get after install.
Useful defaults in requesting-code-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
requesting-code-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for requesting-code-review matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: requesting-code-review is focused, and the summary matches what you get after install.
requesting-code-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for requesting-code-review matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: requesting-code-review is focused, and the summary matches what you get after install.
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