Agent workflow designer
Skill alirezarezvani/claude-skills/engineering/skills/agent-workflow-designer
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.From its SKILL.md
npx -y skills add alirezarezvani/claude-skills --skill agent-workflow-designerAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
SKILL.md
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Agent Workflow Designer
Tier: POWERFUL
Category: Engineering
Domain: Multi-Agent Systems / AI Orchestration
Overview
Design production-grade multi-agent workflows with clear pattern choice, handoff contracts, failure handling, and cost/context controls.
Core Capabilities
- Workflow pattern selection for multi-step agent systems
- Skeleton config generation for fast workflow bootstrapping
- Context and cost discipline across long-running flows
- Error recovery and retry strategy scaffolding
- Documentation pointers for operational pattern tradeoffs
When to Use
- A single prompt is insufficient for task complexity
- You need specialist agents with explicit boundaries
- You want deterministic workflow structure before implementation
- You need validation loops for quality or safety gates
Quick Start
# 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
Pattern Map
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 loop
Detailed templates: references/workflow-patterns.md
Recommended Workflow
- Select pattern based on dependency shape and risk profile.
- Scaffold config via
scripts/workflow_scaffolder.py. - Define handoff contract fields for every edge.
- Add retry/timeouts and output validation gates.
- Dry-run with small context budgets before scaling.
Common Pitfalls
- Over-orchestrating tasks solvable by one well-structured prompt
- Missing timeout/retry policies for external-model calls
- Passing full upstream context instead of targeted artifacts
- Ignoring per-step cost accumulation
Best Practices
- Start with the smallest pattern that can satisfy requirements.
- Keep handoff payloads explicit and bounded.
- Validate intermediate outputs before fan-in synthesis.
- Enforce budget and timeout limits in every step.
What ships with it: 2 files
4.8 KB alongside SKILL.md, 1 of them executable
references/
- workflow-patterns.md1.5 KB
scripts/
- workflow_scaffolder.pyruns3.3 KB