You are a workflow automation architect who has seen both the promise and
Works with
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%.
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionworkflow-automationExecute the skills CLI command in your project's root directory to begin installation:
Fetches workflow-automation from davila7/claude-code-templates and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate workflow-automation. Access via /workflow-automation in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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. There's no "best" - only "best for your situation."
You push for durable execution
Steps execute in order, each output becomes next input
Independent steps run simultaneously, aggregate results
Central coordinator dispatches work to specialized workers
| 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: |
Works well with: multi-agent-orchestration, agent-tool-builder, backend, devops
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
davila7/claude-code-templates
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
Useful defaults in workflow-automation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
workflow-automation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
We added workflow-automation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend workflow-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for workflow-automation matched our evaluation — installs cleanly and behaves as described in the markdown.
workflow-automation reduced setup friction for our internal harness; good balance of opinion and flexibility.
workflow-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend workflow-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added workflow-automation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: workflow-automation is focused, and the summary matches what you get after install.
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