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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 キュレーション済みスキル ★ 注目 品質 優秀 · 90 v1.0.0

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ダウンロード .skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能
.skill ファイルの system_prompt フィールドの実際の内容。
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 Your knowledge of the Agents SDK may be outdated.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)
このスキルを起動するキーワード。クリックでコピーできます。

このスキルにはトリガーワードがありません。

ダウンロードした .skill に含まれるフィールド。
フィールド 説明
formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
install_guide各プラットフォームの導入説明(Coze / Dify / Claude / カスタム)
同じスキルを各プラットフォーム形式で出力できます。
.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
.skillpro 拡張形式。scripts / tools / dependencies / hooks を含む ダウンロード
.json 純粋な JSON 出力。system_prompt とモデル設定のみ ダウンロード
Coze frontmatter 付き Markdown。Coze へのインポート用 ダウンロード
Dify Dify DSL。アプリ作成後にそのままインポート ダウンロード

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