cloudflare-workflows

jezweb/claude-skills · updated Apr 8, 2026

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$npx skills add https://github.com/jezweb/claude-skills --skill cloudflare-workflows
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summary

Durable, long-running workflows with automatic retries, state persistence, and event handling on Cloudflare Workers.

  • Supports three core step types: step.do() for work execution with configurable retries, step.sleep() for delays, and step.waitForEvent() for external event handling with timeouts
  • Automatically persists serializable state across steps and hibernation; prevents 12 documented errors including waitForEvent timeout bugs, I/O context violations, and non-idempotent operation pit
skill.md

Cloudflare Workflows

Status: Production Ready ✅ (GA since April 2025) Last Updated: 2026-01-09 Dependencies: cloudflare-worker-base (for Worker setup) Latest Versions: [email protected], @cloudflare/[email protected]

Recent Updates (2025):

  • April 2025: Workflows GA release - waitForEvent API, Vitest testing, CPU time metrics, 4,500 concurrent instances
  • October 2025: Instance creation rate 10x faster (100/sec), concurrency increased to 10,000
  • 2025 Limits: Max steps 1,024, state persistence 1MB/step (100MB-1GB per instance), event payloads 1MB, CPU time 5 min max
  • Testing: cloudflare:test module with introspectWorkflowInstance, disableSleeps, mockStepResult, mockEvent modifiers
  • Platform: Waiting instances don't count toward concurrency, retention 3-30 days, subrequests 50-1,000

Quick Start (5 Minutes)

# 1. Scaffold project
npm create cloudflare@latest my-workflow -- --template cloudflare/workflows-starter --git --deploy false
cd my-workflow

# 2. Configure wrangler.jsonc
{
  "name": "my-workflow",
  "main": "src/index.ts",
  "compatibility_date": "2025-11-25",
  "workflows": [{
    "name": "my-workflow",
    "binding": "MY_WORKFLOW",
    "class_name": "MyWorkflow"
  }]
}

# 3. Create workflow (src/index.ts)
import { WorkflowEntrypoint, WorkflowStep, WorkflowEvent } from 'cloudflare:workers';

export class MyWorkflow extends WorkflowEntrypoint<Env, Params> {
  async run(event: WorkflowEvent<Params>, step: WorkflowStep) {
    const result = await step.do('process', async () => { /* work */ });
    await step.sleep('wait', '1 hour');
    await step.do('continue', async () => { /* more work */ });
  }
}

# 4. Deploy and test
npm run deploy
npx wrangler workflows instances list my-workflow

CRITICAL: Extends WorkflowEntrypoint, implements run() with step methods, bindings in wrangler.jsonc


Known Issues Prevention

This skill prevents 12 documented errors with Cloudflare Workflows.

Issue #1: waitForEvent Skips Events After Timeout in Local Dev

Error: Events sent after a waitForEvent() timeout are ignored in subsequent waitForEvent() calls Environment: Local development (wrangler dev) only - works correctly in production Source: GitHub Issue #11740

Why It Happens: Bug in miniflare that was fixed in production (May 2025) but not ported to local emulator. After a timeout, the event queue becomes corrupted for that instance.

Prevention:

  • Test waitForEvent timeout scenarios in production/staging, not local dev
  • Avoid chaining multiple waitForEvent() calls where timeouts are expected

Example of Bug:

export class MyWorkflow extends WorkflowEntrypoint<Env, Params> {
  async run(event: WorkflowEvent<Params>, step: WorkflowStep) {
    for (let i = 0; i < 3; i++) {
      try {
        const evt = await step.waitForEvent(`wait-${i}`, {
          type: 'user-action',
          timeout: '5 seconds'
        });
        console.log(`Iteration ${i}: Received event`);
      } catch {
        console.log(`Iteration ${i}: Timeout`);
      }
    }
  }
}
// In wrangler dev:
// - Iteration 1: ✅ receives event
// - Iteration 2: ⏱️ times out (expected)
// - Iteration 3: ❌ does not receive event (BUG - event is sent but ignored)

Status: Known bug, fix pending for miniflare.


Issue #2: getPlatformProxy() Fails With Workflow Bindings

Error: MiniflareCoreError [ERR_RUNTIME_FAILURE]: The Workers runtime failed to start Message: Worker's binding refers to service with named entrypoint, but service has no such entrypoint Source: GitHub Issue #9402

Why It Happens: getPlatformProxy() from wrangler package doesn't support Workflow bindings (similar to how it handles Durable Objects). This blocks Next.js integration and local CLI scripts.

Prevention:

  • Option 1: Comment out workflow bindings when using getPlatformProxy()
  • Option 2: Create separate wrangler.cli.jsonc without workflows for CLI scripts
  • Option 3: Access workflow bindings directly via deployed worker, not proxy
// Workaround: Separate config for CLI scripts
// wrangler.cli.jsonc (no workflows)
{
  "name": "my-worker",
  "main": "src/index.ts",
  "compatibility_date": "2025-01-20"
  // workflows commented out
}

// Use in script:
import { getPlatformProxy } from 'wrangler';
const { env } = await getPlatformProxy({ configPath: './wrangler.cli.jsonc' });

Status: Known limitation, fix planned (filter workflows similar to DOs).


Issue #3: Workflow Instance Lost After Immediate Redirect (Local Dev)

Error: Instance ID returned but instance.not_found when queried Environment: Local development (wrangler dev) only - works correctly in production Source: GitHub Issue #10806

Why It Happens: Returning a redirect immediately after workflow.create() causes request to "soft abort" before workflow initialization completes (single-threaded execution in dev).

Prevention: Use ctx.waitUntil() to ensure workflow initialization completes before redirect:

export default {
  async fetch(req: Request, env: Env, ctx: ExecutionContext): Promise<Response> {
    const workflow = await env.MY_WORKFLOW.create({ params: { userId: '123' } });

    // ✅ Ensure workflow initialization completes
    ctx.waitUntil(workflow.status());

    return Response.redirect('/dashboard', 302);
  }
};

Status: Fixed in recent wrangler versions (post-Sept 2025), but workaround still recommended for compatibility.


Issue #4: Vitest Tests Unreliable in CI Environments

Error: [vitest-worker]: Timeout calling "resolveId" Environment: CI/CD pipelines (GitLab, GitHub Actions) - works locally Source: GitHub Issue #10600

Why It Happens: @cloudflare/vitest-pool-workers has resource constraint issues in CI containers, affecting workflow tests more than other worker types.

Prevention:

  1. Increase testTimeout in vitest config:
    export default defineWorkersConfig({
      test: {
        testTimeout: 60_000 // Default: 5000ms
      }
    });
    
  2. Check CI resource limits (CPU/memory)
  3. Use isolatedStorage: false if not testing storage isolation
  4. Consider testing against deployed instances instead of vitest for critical workflows

Status: Known issue, investigating (Internal: WOR-945).


Issue #5: Instance restart() and terminate() Not Implemented in Local Dev

Error: Error: Not implemented yet when calling instance.restart() or instance.terminate() Environment: Local development (wrangler dev) only - works in production Source: GitHub Issue #11312

Why It Happens: Instance management APIs not yet implemented in miniflare. Additionally, instance status shows running even when workflow is sleeping.

Prevention: Test instance lifecycle management (pause/resume/terminate) in production or staging environment until local dev support is added.

const instance = await env.MY_WORKFLOW.get(instanceId);

// ❌ Fails in wrangler dev
await instance.restart();    // Error: Not implemented yet
await instance.terminate();  // Error: Not implemented yet

// ✅ Works in production

Status: Known limitation, no timeline for local dev support.


Is

how to use cloudflare-workflows

How to use cloudflare-workflows on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add cloudflare-workflows
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jezweb/claude-skills --skill cloudflare-workflows

The skills CLI fetches cloudflare-workflows from GitHub repository jezweb/claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/cloudflare-workflows

Reload or restart Cursor to activate cloudflare-workflows. Access the skill through slash commands (e.g., /cloudflare-workflows) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.761 reviews
  • Kaira Ramirez· Dec 20, 2024

    Registry listing for cloudflare-workflows matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Henry Johnson· Dec 20, 2024

    Solid pick for teams standardizing on skills: cloudflare-workflows is focused, and the summary matches what you get after install.

  • Sakura Martinez· Dec 8, 2024

    Registry listing for cloudflare-workflows matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Chen Jackson· Dec 4, 2024

    cloudflare-workflows fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • William Liu· Nov 27, 2024

    Useful defaults in cloudflare-workflows — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Olivia Okafor· Nov 23, 2024

    cloudflare-workflows has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Arjun Li· Nov 11, 2024

    Useful defaults in cloudflare-workflows — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Henry Garcia· Nov 11, 2024

    We added cloudflare-workflows from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Rahul Santra· Nov 7, 2024

    cloudflare-workflows is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Zara Sharma· Nov 3, 2024

    Keeps context tight: cloudflare-workflows is the kind of skill you can hand to a new teammate without a long onboarding doc.

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