Agent workflow designer

Skill alirezarezvani/claude-skills/engineering/skills/agent-workflow-designer

345 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 330+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8 more coding agents — engineering, marketing, product, compliance, C-level advisory, research, business operations, commercial & finance, and your daily productivity skills.

Install

npx -y skills add alirezarezvani/claude-skills --skill agent-workflow-designer

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What its author says it does

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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.

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 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.