Coordinate multi-agent workflows: sequential, parallel, and iterative patterns. Defines agent handoffs, dependencies, communication protocols, and integration. Use when designing multi-agent workflows, coordinating agent handoffs, planning agent dependencies, or building complex agent pipelines.
/plugin marketplace add laurigates/claude-plugins/plugin install agent-patterns-plugin@lgates-claude-pluginsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
Coordination patterns for sequential, parallel, and iterative agent workflows. Defines how agents work together, communicate findings, and maintain context across handoffs in multi-agent systems.
Automatically apply this skill when:
Two complementary layers work together:
1. Transparency Layer (File-Based)
2. Intelligence Layer (Knowledge Graph)
Before starting work, agents MUST:
Example Flow:
User delegates to python-developer:
1. Read current-workflow.md → "Building REST API"
2. Read agent-queue.md → "research-assistant completed"
3. Read inter-agent-context.json → "Tech: FastAPI + PostgreSQL"
4. Read research-assistant-output.md → "Requirements defined"
5. Begin implementation with full context
Continuously communicate state:
Produce standardized results:
Agents work one after another, each building on previous work.
Pattern Structure:
Agent A completes → Writes output
↓
Agent B reads A's output → Starts work → Writes output
↓
Agent C reads A's and B's outputs → Starts work
When to use:
Example Workflow:
Research Assistant (30 min)
↓ (passes requirements)
Python Developer (90 min)
↓ (passes implementation)
Test Architect (45 min)
↓ (passes test suite)
Documentation Writer (30 min)
Best Practices:
Multiple agents work simultaneously on independent tasks.
Pattern Structure:
┌→ Agent A → Output A
Start → ├→ Agent B → Output B → Integration Agent
└→ Agent C → Output C
When to use:
Example Workflow:
Requirements Defined
├→ Backend Developer (API)
├→ Frontend Developer (UI)
└→ Database Architect (Schema)
↓
Integration Tester (Verify all parts work together)
Best Practices:
Shared Contract Example:
{
"api_contract": {
"/api/users": {
"GET": "returns user list",
"POST": "creates user"
}
},
"data_models": {
"User": {
"id": "string",
"name": "string",
"email": "string"
}
}
}
Agent revisits work based on feedback from other agents.
Pattern Structure:
Agent A → Agent B (reviews) → Issues found
↑ ↓
←───────── Feedback ────────────↓
When to use:
Example Workflow:
Developer → Code Review → Issues Found
↑ ↓
←── Fix Issues ──────────↓
Security Auditor → Vulnerabilities Found
↑ ↓
Developer ←── Apply Fixes ───↓
Best Practices:
Feedback Format:
## Review Feedback
### Critical Issues (Must Fix)
1. SQL injection vulnerability in `/api/users` line 45
2. Missing authentication on DELETE endpoint
### Improvements (Should Fix)
1. Add input validation for email format
2. Implement rate limiting
### Suggestions (Could Improve)
1. Consider caching for performance
2. Add more descriptive error messages
Combines multiple patterns for complex workflows.
Example Structure:
Sequential Start:
Research → Architecture Design
↓
Parallel Development:
├→ Backend Team
├→ Frontend Team
└→ QA Test Planning
↓
Sequential Integration:
Integration → Testing
↓
Iterative Refinement:
Review ↔ Fixes
When to use:
Hard Dependencies (Must Complete First):
{
"agent": "test-architect",
"depends_on": ["python-developer"],
"reason": "Cannot test code that doesn't exist"
}
Soft Dependencies (Preferred Order):
{
"agent": "documentation-writer",
"prefers_after": ["test-architect"],
"reason": "Better docs with test examples"
}
Status Broadcasting:
Handoff Requirements:
When agents disagree:
Precedence Rules:
Security Auditor > All Others (security issues)
Architect > Developers (design decisions)
Senior > Junior (experience hierarchy)
Later > Earlier (recent context)
agent-file-coordination, multi-agent-workflowsagent-context-management (coordination sections)Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.