Agent Workflow Designer

What This Skill Does

Agent Workflow Designer helps design production-grade multi-agent workflows with clear pattern choices, handoff contracts, and failure handling. It provides tools for cost/context control and error recovery. This skill is useful for engineers who need deterministic workflow structures before implementation.

When to Use

• Design multi-step agent systems.
• Select workflow patterns for agent systems.
• Generate skeleton configs for fast workflow bootstrapping.
• Enforce context and cost discipline across long-running flows.
• Implement error recovery and retry strategies.
• Create validation loops for quality or safety gates.

Key Features

• Offers workflow pattern selection for multi-step systems.
• Generates skeleton configs for fast bootstrapping.
• Enforces context and cost discipline.
• Scaffolds error recovery and retry strategies.
• Provides documentation pointers for operational pattern tradeoffs.
• Supports sequential, parallel, router, orchestrator, and evaluator patterns.

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 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

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.
• 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 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

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.