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agents-sdk

Build, debug, or review Cloudflare Agents SDK applications using the agents package.

DeepseekModel キュレーション済みスキル 品質 優秀 · 90 v1.0.0

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https://deepseekmodel.com/api/download.php?id=cloudflare-skills-skills-agents-sdk-skill-md&format=skill
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, debug, or review Cloudflare Agents SDK applications using the agents package. Cloudflare Agents SDK Your knowledge of the Agents SDK may be outdated. Prefer retrieval over pre-training for any Agents SDK task. Retrieval Sources Cloudflare docs: https://developers.cloudflare.com/agents/ Topic Docs URL Use for Getting started Quick start First agent, project setup Adding to existing project Add to existing project Install into existing Workers app Configuration Configuration wrangler.jsonc , bindings, assets, deployment Agent class Agents API Agent lifecycle, patterns, pitfalls State Store and sync state setState , validateStateChange , persistence Routing Routing URL patterns, routeAgentRequest Callable methods Callable methods @callable , RPC, streaming, timeouts Scheduling Schedule tasks schedule() , scheduleEvery() , cron Workflows Run workflows AgentWorkflow , durable multi-step tasks HTTP/WebSockets WebSockets Lifecycle hooks, hibernation Chat agents Chat agents AIChatAgent , streaming, tools, persistence Client SDK Client SDK useAgent , AgentClient , state, RPC, HTTP Client tools Client tools Client-side tools, autoContinueAfterToolResult Server-driven messages Autonomous responses saveMessages , waitUntilStable , server-initiated turns Resumable streaming Chat agents Stream recovery on disconnect Email Email Email routing, secure reply resolver MCP client MCP client Connecting to MCP servers MCP server MCP server Building MCP servers with createMcpHandler MCP transports MCP transports Streamable HTTP, SSE, RPC transport options Securing MCP servers Securing MCP OAuth, proxy MCP, hardening Human-in-the-loop Human-in-the-loop Workflow approvals, elicitation, timeout handling Durable execution Durable execution runFiber() , stash() , surviving DO eviction Queue Queue Built-in FIFO queue, queue() Retries Retries this.retry() , backoff/jitter Observability Observability Diagnostics-channel events Push notifications Push notifications Web Push + VAPID from agents Webhooks Webhooks Receiving external webhooks Cross-domain auth Cross-domain auth WebSocket auth, tokens, CORS Readonly connections Readonly shouldConnectionBeReadonly Voice Voice Experimental STT/TTS, withVoice Browse the web Browser tools Experimental CDP browser automation Think Think Experimental higher-level chat agent class Migrations AI SDK v5 , AI SDK v6 Upgrading @cloudflare/ai-chat Capabilities The Agents SDK provides: Persistent state — SQLite-backed, auto-synced to clients via setState Callable RPC — @callable() methods invoked over WebSocket Scheduling — One-time, recurring ( scheduleEvery ), and cron tasks Workflows — Durable multi-step background processing via AgentWorkflow Durable execution — runFiber() / stash() for work that survives DO eviction Queue — Built-in FIFO queue with retries via queue() Retries — this.retry() with exponential backoff and jitter MCP integration — Connect to MCP servers or build your own with createMcpHandler Email handling — Receive and reply to emails with secure routing Streaming chat — AIChatAgent with resumable streams, message persistence, tools Server-driven messages — saveMessages , waitUntilStable for proactive agent turns React hooks — useAgent , useAgentChat for client apps Observability — diagnostics_channel events for state, RPC, schedule, lifecycle Push notifications — Web Push + VAPID delivery from agents Webhooks — Receive and verify external webhooks Voice (experimental) — STT/TTS via @cloudflare/voice Browser tools (experimental) — CDP-powered browsing via agents/browser Think (experimental) — Higher-level chat agent via @cloudflare/think FIRST: Verify Installation npm ls agents # Should show agents package If not installed: npm install agents For chat agents: npm install agents @cloudflare/ai-chat ai @ai-sdk/react Wrangler Configuration { "compatibility_flags" : [ "nodejs_compat" ] , "durable_objects" : { "bindings" : [ { "name" : "MyAgent" , "class_name" : "MyAgent" } ] } , "migrations" : [ { "tag" : "v1" , "new_sqlite_classes" : [ "MyAgent" ] } ] } Gotchas: Do NOT enable experimentalDecorators in tsconfig (breaks @callable ) Never edit old migrations — always add new tags Each agent class needs its own DO binding + migration entry Add "ai": { "binding": "AI" } for Workers AI Agent Class import { Agent , routeAgentRequest, callable } from "agents" ; type State = { count : number }; export class Counter extends Agent < Env , State > { initialState = { count : 0 }; validateStateChange ( nextState : State , source : Connection | "server" ) { if (nextState. count < 0 ) throw new Error ( "Count cannot be negative" ); } 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" }) Custom routing: use getAgentByName(env.MyAgent, "instance-id") then agent.fetch(request) . 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) Durable fiber await this.runFiber("name", async (ctx) => { ... }) Enqueue work this.queue("handler", payload) Retry with backoff await this.retry(fn, { maxAttempts: 5 }) Broadcast to clients this.broadcast(message) Get connections this.getConnections(tag?) React Client Read client-sdk.md for client selection and current connection examples. For chat UI and tools, also read streaming-chat.md . References Core references/state-scheduling.md — State persistence, scheduling, SQL references/callable.md — RPC methods, streaming, timeouts references/routing.md — URL patterns, custom routing, getAgentByName references/configuration.md — Wrangler config, bindings, Vite setup Chat & Streaming references/streaming-chat.md — AIChatAgent, resumable streams, tools references/client-sdk.md — useAgent , useAgentChat , AgentClient references/server-driven-messages.md — Trigger patterns, saveMessages references/human-in-the-loop.md — Approval flows, needsApproval Background Processing references/workflows.md — Durable Workflows integration references/durable-execution.md — runFiber , stash , surviving eviction references/queue-retries.md — Built-in queue, retry with backoff Integrations references/mcp.md — MCP client and server, transports, securing references/email.md — Email routing and handling
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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)
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.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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