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agents-sdk

Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks.

DeepseekModel 官方收录技能 ★ 精选 质量 优秀 · 90 v1.0.0

获取

https://deepseekmodel.com/api/download.php?id=anomalyco-opencode-packages-opencode-test-fixture-skills-agents-sdk-skill-md&format=skill
下载 .skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用
.skill 文件中 system_prompt 字段的实际内容。
name agents-sdk description Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents, durable workflows, real-time WebSocket apps, scheduled tasks, MCP servers, or chat applications. Covers Agent class, state management, callable RPC, Workflows integration, and React hooks. Cloudflare Agents SDK STOP. Your knowledge of the Agents SDK may be outdated. Prefer retrieval over pre-training for any Agents SDK task. Documentation 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 references/workflows.md - Durable Workflows integration references/callable.md - RPC methods, streaming, timeouts references/state-scheduling.md - State persistence, scheduling references/streaming-chat.md - AIChatAgent, resumable streams references/mcp.md - MCP server integration references/email.md - Email routing and handling references/codemode.md - Code Mode (experimental)
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下载的 .skill 包内含以下字段。
字段 说明
format格式标识(skill/v1)
skill_id技能唯一 ID
name技能名称
version版本号
description技能描述
category所属分类(数组)
trigger_words触发词列表
tags标签列表
source来源标识
source_url来源链接(本页地址)
exported_at导出时间(每次下载生成)
system_prompt系统提示词正文
model_config模型参数:provider / model / temperature / max_tokens / top_p
examples示例
install_guide各平台导入说明(Coze / Dify / Claude / 自定义框架)
同一份技能可按不同平台格式导出。
.skill 标准格式,含 system_prompt 与 model_config,导入任意 Agent 框架即可使用 下载
.skillpro 增强格式,额外含脚本 / 工具 / 依赖 / 钩子占位 下载
.json 纯 JSON 导出,只含 system_prompt 与模型参数 下载
Coze 带 frontmatter 的 Markdown,Coze 平台导入用 下载
Dify Dify DSL,创建应用后直接导入 下载

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