KS
Killer-Skills

vercel-composition-patterns — Categories.community

v1.0.0
GitHub

About this Skill

Essential for React Code Generation Agents specializing in scalable component architecture and AI-assisted refactoring. Agent OS, with Agentic Mesh capabilities with Qorelogic governance and recursive learning protocol intended for native integration with Zo.computer

MythologIQ MythologIQ
[0]
[0]
Updated: 2/24/2026

Quality Score

Top 5%
44
Excellent
Based on code quality & docs
Installation
SYS Universal Install (Auto-Detect)
Cursor IDE Windsurf IDE VS Code IDE
> npx killer-skills add MythologIQ/Zo-Qore/vercel-composition-patterns

Agent Capability Analysis

The vercel-composition-patterns MCP Server by MythologIQ is an open-source Categories.community integration for Claude and other AI agents, enabling seamless task automation and capability expansion.

Ideal Agent Persona

Essential for React Code Generation Agents specializing in scalable component architecture and AI-assisted refactoring.

Core Value

Enables agents to generate and refactor React components using advanced composition patterns like compound components and state lifting, directly addressing boolean prop proliferation for more maintainable codebases. Native integration with Zo.computer provides Agentic Mesh capabilities with Qorelogic governance and recursive learning protocols.

Capabilities Granted for vercel-composition-patterns MCP Server

Refactoring components with excessive boolean props
Building reusable component libraries
Designing flexible component APIs
Reviewing component architecture for scalability

! Prerequisites & Limits

  • React-specific patterns only
  • Requires understanding of component composition
  • Primarily benefits frontend development agents
Project
SKILL.md
2.6 KB
.cursorrules
1.2 KB
package.json
240 B
Ready
UTF-8

# Tags

[No tags]
SKILL.md
Readonly

React Composition Patterns

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.

When to Apply

Reference these guidelines when:

  • Refactoring components with many boolean props
  • Building reusable component libraries
  • Designing flexible component APIs
  • Reviewing component architecture
  • Working with compound components or context providers

Rule Categories by Priority

PriorityCategoryImpactPrefix
1Component ArchitectureHIGHarchitecture-
2State ManagementMEDIUMstate-
3Implementation PatternsMEDIUMpatterns-
4React 19 APIsMEDIUMreact19-

Quick Reference

1. Component Architecture (HIGH)

  • architecture-avoid-boolean-props - Don't add boolean props to customize behavior; use composition
  • architecture-compound-components - Structure complex components with shared context

2. State Management (MEDIUM)

  • state-decouple-implementation - Provider is the only place that knows how state is managed
  • state-context-interface - Define generic interface with state, actions, meta for dependency injection
  • state-lift-state - Move state into provider components for sibling access

3. Implementation Patterns (MEDIUM)

  • patterns-explicit-variants - Create explicit variant components instead of boolean modes
  • patterns-children-over-render-props - Use children for composition instead of renderX props

4. React 19 APIs (MEDIUM)

⚠️ React 19+ only. Skip this section if using React 18 or earlier.

  • react19-no-forwardref - Don't use forwardRef; use use() instead of useContext()

How to Use

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:

  • Brief explanation of why it matters
  • Incorrect code example with explanation
  • Correct code example with explanation
  • Additional context and references

Full Compiled Document

For the complete guide with all rules expanded: AGENTS.md

Scope Boundary

In scope

  • Component API architecture patterns (compound components, render props, context composition).

Out of scope

  • Runtime performance/bundle optimization as the primary objective (use vercel-react-best-practices).

Related Skills

Looking for an alternative to vercel-composition-patterns or building a Categories.community AI Agent? Explore these related open-source MCP Servers.

View All

widget-generator

Logo of f
f

widget-generator is an open-source AI agent skill for creating widget plugins that are injected into prompt feeds on prompts.chat. It supports two rendering modes: standard prompt widgets using default PromptCard styling and custom render widgets built as full React components.

149.6k
0
Design

chat-sdk

Logo of lobehub
lobehub

chat-sdk is a unified TypeScript SDK for building chat bots across multiple platforms, providing a single interface for deploying bot logic.

73.0k
0
Communication

zustand

Logo of lobehub
lobehub

The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.

72.8k
0
Communication

data-fetching

Logo of lobehub
lobehub

The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.

72.8k
0
Communication