agent-workflow-designer – Agents & Automation skill for AI agents
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 su
Install the agent-workflow-designer skill with one command
Pick the tool you use, copy the command and paste it in your terminal. The skill lands in that tool's skills folder and is ready in your next session.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/agent-workflow-designer-c3ed7.tgz | tar xz -C ~/.claude/skills
Call it in Claude Code: /agent-workflow-designer – then describe the task you want done.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/agent-workflow-designer-c3ed7.tgz | tar xz -C ~/.codex/skills
Call it in Codex: $agent-workflow-designer – then describe the task you want done.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/agent-workflow-designer-c3ed7.tgz | tar xz -C ~/.hermes/skills
Call it in Hermes Agent: /agent-workflow-designer – then describe the task you want done.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/agent-workflow-designer-c3ed7.tgz | tar xz -C ~/.deepcode/skills
Call it in DeepSeek: /agent-workflow-designer – then describe the task you want done.
SKILL.md content
Agent Workflow Designer
Tier: POWERFUL
Category: Engineering
Domain: Multi-Agent Systems / AI Orchestration
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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
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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
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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
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Recommended Workflow
1. Select pattern based on dependency shape and risk profile.
2. Scaffold config via scripts/workflow_scaffolder.py.
3. Define handoff contract fields for every edge.
4. Add retry/timeouts and output validation gates.
5. Dry-run with small context budgets before scaling.
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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
1. Start with the smallest pattern that can satisfy requirements.
2. Keep handoff payloads explicit and bounded.
3. Validate intermediate outputs before fan-in synthesis.
4. Enforce budget and timeout limits in every step.
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