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.
1---2name: agent-workflow-designer3description: Agent Workflow Designer4---56# Agent Workflow Designer78**Tier:** POWERFUL 9**Category:** Engineering 10**Domain:** Multi-Agent Systems / AI Orchestration1112---1314## Overview1516Design production-grade multi-agent workflows with clear pattern choice, handoff contracts, failure handling, and cost/context controls.1718## Core Capabilities1920- Workflow pattern selection for multi-step agent systems21- Skeleton config generation for fast workflow bootstrapping22- Context and cost discipline across long-running flows23- Error recovery and retry strategy scaffolding24- Documentation pointers for operational pattern tradeoffs2526---2728## When to Use2930- A single prompt is insufficient for task complexity31- You need specialist agents with explicit boundaries32- You want deterministic workflow structure before implementation33- You need validation loops for quality or safety gates3435---3637## Quick Start3839```bash40# Generate a sequential workflow skeleton41python3 scripts/workflow_scaffolder.py sequential --name content-pipeline4243# Generate an orchestrator workflow and save it44python3 scripts/workflow_scaffolder.py orchestrator --name incident-triage --output workflows/incident-triage.json45```4647---4849## Pattern Map5051- `sequential`: strict step-by-step dependency chain52- `parallel`: fan-out/fan-in for independent subtasks53- `router`: dispatch by intent/type with fallback54- `orchestrator`: planner coordinates specialists with dependencies55- `evaluator`: generator + quality gate loop5657Detailed templates: `references/workflow-patterns.md`5859---6061## Recommended Workflow62631. Select pattern based on dependency shape and risk profile.642. Scaffold config via `scripts/workflow_scaffolder.py`.653. Define handoff contract fields for every edge.664. Add retry/timeouts and output validation gates.675. Dry-run with small context budgets before scaling.6869---7071## Common Pitfalls7273- Over-orchestrating tasks solvable by one well-structured prompt74- Missing timeout/retry policies for external-model calls75- Passing full upstream context instead of targeted artifacts76- Ignoring per-step cost accumulation7778## Best Practices79801. Start with the smallest pattern that can satisfy requirements.812. Keep handoff payloads explicit and bounded.823. Validate intermediate outputs before fan-in synthesis.834. Enforce budget and timeout limits in every step.
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Agent Workflow Designer It is listed under AI & ML on SkillMD.
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DylanCkawalec (@dylanckawalec) published this skill. Their other Agent Skills are listed on their SkillMD profile.