Design production-grade multi-agent workflows with clear pattern choice (sequential, parallel, hierarchical), handoff contracts, failure handling, and cost/context controls. Use when architecting a multi-step agent pipeline, choosing between single-agent vs multi-agent approaches, or refactoring an LLM workflow that suffers from context bloat or unreliable handoffs.
cd ~/.claude/skills
git clone https://github.com/alirezarezvani/claude-skills.git claude-skills mkdir -p ~/.claude/skills/agent-workflow-designer
curl -fsSL https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/.gemini/skills/agent-workflow-designer/SKILL.md \
-o ~/.claude/skills/agent-workflow-designer/SKILL.md Tier: POWERFUL
Category: Engineering
Domain: Multi-Agent Systems / AI Orchestration
Design production-grade multi-agent workflows with clear pattern choice, handoff contracts, failure handling, and cost/context controls.
# Generate a sequential workflow skeleton
python3 scripts/workflow_scaffolder.py sequential --name content-pipeline
# Generate an orchestrator workflow and save it
python3 scripts/workflow_scaffolder.py orchestrator --name incident-triage --output workflows/incident-triage.json
sequential: strict step-by-step dependency chainparallel: fan-out/fan-in for independent subtasksrouter: dispatch by intent/type with fallbackorchestrator: planner coordinates specialists with dependenciesevaluator: generator + quality gate loopDetailed templates: references/workflow-patterns.md
scripts/workflow_scaffolder.py.You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback
Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions