Agent skill · product strategy · daffy0208
Multi-Agent Architect
Design and orchestrate multi-agent systems. Use when building complex AI systems requiring specialization, parallel processing, or collaborative problem-solving. Covers agent coordination, communication patterns, and task delegation strategies.
Why this skill is useful
Provides specific coordination patterns and communication strategies for multi-agent systems that the AI wouldn't reliably generate on its own.
What it needs
About 5k tokens when loaded. Last updated 2025-12-25. 33 stars on the source repository.
What this skill does
Multi-Agent Architect Design systems where multiple specialized agents collaborate to solve complex problems. Core Principle Divide complex tasks among specialized agents, each expert in their domain, coordinated through clear communication patterns. When to Use Multi-Agent Systems Use Multi-Agent When: ✅ Task requires multiple specializations (research + writing + coding) ✅ Parallel processing speeds up solution (independent subtasks) ✅ Need self-correction through peer review ✅ Complex workflows with decision points ✅ Scaling single-agent becomes unwieldy Don't Use Multi-Agent When: ❌ Single agent can handle task efficiently ❌ Task is simple and linear ❌ Communication overhead > parallelization benefit ❌ Team lacks multi-agent debugging expertise --- Multi-Agent Patterns Pattern 1: Sequential Pipeline Use: Multi-step workflow where each agent builds on previous Example: Research report generation 1. Researcher: Gather sources 2. Analyst: Synthesize findings 3. Writer: Draft report 4. Editor: Refine and format Pros: Clear dependencies, easy to debug Cons: Sequential (no parallelization), bottlenecks --- Pattern 2: Hierarchical (Manager-Worker) Use: Complex task broken into parallel subtasks Example: Market research across competitors Manager: Decompose into per-competitor analysis Workers: Research competitor A, B, C in parallel Aggregator: Combine findings Pros: Parallelization, specialization Cons: Manager complexity, coordination overhead --- Pattern 3: Peer Collaboration (Round Table) Use: Multiple perspectives improve quality Example: Code generation with review 1. Coder: Write initial code 2. Reviewer: Check for issues 3. Tester: Validate functionality 4. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills daffy0208/multi-agent-architect