Composition patterns for building flexible, maintainable React components. Avoid
Works with
boolean prop proliferation by using compound components, lifting state, and
composing internals. These patterns make codebases easier for both humans and AI
agents to work with as they scale.
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionvercel-composition-patternsExecute the skills CLI command in your project's root directory to begin installation:
Fetches vercel-composition-patterns from vercel-labs/claude-skills 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 vercel-composition-patterns. Access via /vercel-composition-patterns 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.
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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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Composition patterns for building flexible, maintainable React components. Avoid boolean prop proliferation by using compound components, lifting state, and composing internals. These patterns make codebases easier for both humans and AI agents to work with as they scale.
Reference these guidelines when:
| Priority | Category | Impact | Prefix |
|---|---|---|---|
| 1 | Component Architecture | HIGH | architecture- |
| 2 | State Management | MEDIUM | state- |
| 3 | Implementation Patterns | MEDIUM | patterns- |
| 4 | React 19 APIs | MEDIUM | react19- |
architecture-avoid-boolean-props - Don't add boolean props to customize
behavior; use compositionarchitecture-compound-components - Structure complex components with shared
contextstate-decouple-implementation - Provider is the only place that knows how
state is managedstate-context-interface - Define generic interface with state, actions, meta
for dependency injectionstate-lift-state - Move state into provider components for sibling accesspatterns-explicit-variants - Create explicit variant components instead of
boolean modespatterns-children-over-render-props - Use children for composition instead
of renderX props⚠️ React 19+ only. Skip this section if using React 18 or earlier.
react19-no-forwardref - Don't use forwardRef; use use() instead of useContext()Read individual rule files for detailed explanations and code examples:
rules/architecture-avoid-boolean-props.md
rules/state-context-interface.md
Each rule file contains:
For the complete guide with all rules expanded: AGENTS.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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
vercel-composition-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
vercel-composition-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend vercel-composition-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for vercel-composition-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
vercel-composition-patterns fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
vercel-composition-patterns reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend vercel-composition-patterns for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
vercel-composition-patterns is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in vercel-composition-patterns — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for vercel-composition-patterns matched our evaluation — installs cleanly and behaves as described in the markdown.
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