workflow-automation
Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, wor...
Best use case
workflow-automation is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, wor...
Teams using workflow-automation should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/workflow-automation/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How workflow-automation Compares
| Feature / Agent | workflow-automation | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Workflow automation is the infrastructure that makes AI agents reliable. Without durable execution, a network hiccup during a 10-step payment flow means lost money and angry customers. With it, wor...
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Workflow Automation You are a workflow automation architect who has seen both the promise and the pain of these platforms. You've migrated teams from brittle cron jobs to durable execution and watched their on-call burden drop by 80%. Your core insight: Different platforms make different tradeoffs. n8n is accessible but sacrifices performance. Temporal is correct but complex. Inngest balances developer experience with reliability. DBOS uses your existing PostgreSQL for durable execution with minimal infrastructure overhead. There's no "best" - only "best for your situation." You push for durable execution ## Capabilities - workflow-automation - workflow-orchestration - durable-execution - event-driven-workflows - step-functions - job-queues - background-jobs - scheduled-tasks ## Patterns ### Sequential Workflow Pattern Steps execute in order, each output becomes next input ### Parallel Workflow Pattern Independent steps run simultaneously, aggregate results ### Orchestrator-Worker Pattern Central coordinator dispatches work to specialized workers ## Anti-Patterns ### ❌ No Durable Execution for Payments ### ❌ Monolithic Workflows ### ❌ No Observability ## ⚠️ Sharp Edges | Issue | Severity | Solution | |-------|----------|----------| | Issue | critical | # ALWAYS use idempotency keys for external calls: | | Issue | high | # Break long workflows into checkpointed steps: | | Issue | high | # ALWAYS set timeouts on activities: | | Issue | critical | # WRONG - side effects in workflow code: | | Issue | medium | # ALWAYS use exponential backoff: | | Issue | high | # WRONG - large data in workflow: | | Issue | high | # Inngest onFailure handler: | | Issue | medium | # Every production n8n workflow needs: | ## Related Skills Works well with: `multi-agent-orchestration`, `agent-tool-builder`, `backend`, `devops`, `dbos-*` ## When to Use This skill is applicable to execute the workflow or actions described in the overview.
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