agent-workflow-designer

name	agent-workflow-designer
description	A single prompt is insufficient for task complexity
executor	HYBRID
skill_id	engineering.cs-engineering.agent-workflow-designer
status	ADOPTED
security	{"level":"standard","pii":false,"approval_required":false}
anchors	["engineering","agent","workflow","design"]
tier	2
input_schema	[{"name":"code_or_task","type":"string","description":"Code snippet, script, or task description to process","required":true},{"name":"context","type":"string","description":"Additional context or background information","required":false}]
output_schema	[{"name":"plan","type":"string","description":"Strategic plan or design document"},{"name":"next_steps","type":"array","description":"List of recommended next steps"}]

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

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Pattern Map

• sequential: strict step-by-step dependency chain
• parallel: fan-out/fan-in for independent subtasks
• router: dispatch by intent/type with fallback
• orchestrator: planner coordinates specialists with dependencies
• evaluator: 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