agents-sdk

cloudflare/skills · updated Apr 8, 2026

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$npx skills add https://github.com/cloudflare/skills --skill agents-sdk
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summary

Build stateful AI agents on Cloudflare Workers with persistent state, RPC methods, scheduling, and workflow orchestration.

  • Core features include SQLite-backed state management, callable RPC methods via @callable() , one-time and recurring task scheduling, and durable multi-step workflows
  • Supports MCP server integration (both client and server modes), email routing with secure replies, and streaming chat with resumable streams on disconnect
  • Includes React hooks ( useAgent , useAgentCh
skill.md

Cloudflare Agents SDK

Your knowledge of the Agents SDK may be outdated. Prefer retrieval over pre-training for any Agents SDK task.

Retrieval Sources

Fetch current docs from https://github.com/cloudflare/agents/tree/main/docs before implementing.

Topic Doc Use for
Getting started docs/getting-started.md First agent, project setup
State docs/state.md setState, validateStateChange, persistence
Routing docs/routing.md URL patterns, routeAgentRequest, basePath
Callable methods docs/callable-methods.md @callable, RPC, streaming, timeouts
Scheduling docs/scheduling.md schedule(), scheduleEvery(), cron
Workflows docs/workflows.md AgentWorkflow, durable multi-step tasks
HTTP/WebSockets docs/http-websockets.md Lifecycle hooks, hibernation
Email docs/email.md Email routing, secure reply resolver
MCP client docs/mcp-client.md Connecting to MCP servers
MCP server docs/mcp-servers.md Building MCP servers with McpAgent
Client SDK docs/client-sdk.md useAgent, useAgentChat, React hooks
Human-in-the-loop docs/human-in-the-loop.md Approval flows, pausing workflows
Resumable streaming docs/resumable-streaming.md Stream recovery on disconnect

Cloudflare docs: https://developers.cloudflare.com/agents/

Capabilities

The Agents SDK provides:

  • Persistent state - SQLite-backed, auto-synced to clients
  • Callable RPC - @callable() methods invoked over WebSocket
  • Scheduling - One-time, recurring (scheduleEvery), and cron tasks
  • Workflows - Durable multi-step background processing via AgentWorkflow
  • MCP integration - Connect to MCP servers or build your own with McpAgent
  • Email handling - Receive and reply to emails with secure routing
  • Streaming chat - AIChatAgent with resumable streams
  • React hooks - useAgent, useAgentChat for client apps

FIRST: Verify Installation

npm ls agents  # Should show agents package

If not installed:

npm install agents

Wrangler Configuration

{
  "durable_objects": {
    "bindings": [{ "name": "MyAgent", "class_name": "MyAgent" }]
  },
  "migrations": [{ "tag": "v1", "new_sqlite_classes": ["MyAgent"] }]
}

Agent Class

import { Agent, routeAgentRequest, callable } from "agents";

type State = { count: number };

export class Counter extends Agent<Env, State> {
  initialState = { count: 0 };

  // Validation hook - runs before state persists (sync, throwing rejects the update)
  validateStateChange(nextState: State, source: Connection | "server") {
    if (nextState.count < 0) throw new Error("Count cannot be negative");
  }

  // Notification hook - runs after state persists (async, non-blocking)
  onStateUpdate(state: State, source: Connection | "server") {
    console.log("State updated:", state);
  }

  @callable()
  increment() {
    this.setState({ count: this.state.count + 1 });
    return this.state.count;
  }
}

export default {
  fetch: (req, env) => routeAgentRequest(req, env) ?? new Response("Not found", { status: 404 })
};

Routing

Requests route to /agents/{agent-name}/{instance-name}:

Class URL
Counter /agents/counter/user-123
ChatRoom /agents/chat-room/lobby

Client: useAgent({ agent: "Counter", name: "user-123" })

Core APIs

Task API
Read state this.state.count
Write state this.setState({ count: 1 })
SQL query this.sql`SELECT * FROM users WHERE id = ${id}`
Schedule (delay) await this.schedule(60, "task", payload)
Schedule (cron) await this.schedule("0 * * * *", "task", payload)
Schedule (interval) await this.scheduleEvery(30, "poll")
RPC method @callable() myMethod() { ... }
Streaming RPC @callable({ streaming: true }) stream(res) { ... }
Start workflow await this.runWorkflow("ProcessingWorkflow", params)

React Client

import { useAgent } from "agents/react";

function App() {
  const [state, setLocalState] = useState({ count: 0 });

  const agent = useAgent({
    agent: "Counter",
    name: "my-instance",
    onStateUpdate: (newState) => setLocalState(newState),
    onIdentity: (name, agentType) => console.log(`Connected to ${name}`)
  });

  return (
    <button onClick={() => agent.setState({ count: state.count + 1 })}>
      Count: {state.count}
    </button>
  );
}

References

how to use agents-sdk

How to use agents-sdk 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 agents-sdk
2

Execute installation command

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

$npx skills add https://github.com/cloudflare/skills --skill agents-sdk

The skills CLI fetches agents-sdk from GitHub repository cloudflare/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/agents-sdk

Reload or restart Cursor to activate agents-sdk. Access the skill through slash commands (e.g., /agents-sdk) 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.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

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

Ratings

4.655 reviews
  • Xiao Martin· Dec 20, 2024

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

  • Tariq Torres· Dec 16, 2024

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

  • Ira Verma· Dec 12, 2024

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

  • Li Torres· Dec 8, 2024

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

  • Chen Jain· Nov 27, 2024

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

  • Neel Chen· Nov 11, 2024

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

  • Tariq Khan· Nov 7, 2024

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

  • Ira Thomas· Nov 3, 2024

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

  • Amina Mehta· Oct 26, 2024

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

  • Ira Choi· Oct 22, 2024

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

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