API安装
- 作者仓库星标 164,300
- 作者更新于 实时读取
- 作者仓库 opencode
- 领域
- AI 智能
- 兼容 Agent
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- 信任分
- 88 / 100 · 社区维护
- 作者 / 版本 / 许可
- @anomalyco · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 即装即用
- 是否需要外部 API Key
- 不需要
- 兼容的系统
- macOS · Linux · Windows
- 底层运行要求
- 无特殊要求
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- 网络行为
- 允许外网请求
- 安装命令数
- 26 条
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: agents-sdk
description: Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents…
category: AI 智能
runtime: 无特殊运行时
---
# agents-sdk 输出预览
## PART A: 任务判断
- 适用问题:提示词、Agent 工作流、模型评估或自动化推理。
- 输入要求:目标材料、限制条件、期望输出和验收方式。
- 证据边界:围绕“Documentation / Capabilities / FIRST: Verify Installation”读取原文规则,不把推断写成作者承诺。
## PART B: 执行结果
- **01** 任务判断:确认你的需求是否属于提示词、Agent 工作流、模型评估或自动化推理,并标出输入、限制和预期结果。
- **02** 执行计划:优先按“Documentation / Capabilities / FIRST: Verify Installation”拆成步骤,说明每一步会读取什么、修改什么、产出什么。
- **03** 交付结果:给出可复制的命令、文件改动、检查清单或内容草稿,并说明如何继续迭代。
- **04** 风险边界:结合 读取文件、写入/修改文件、会按任务需要访问外部网络、通常不需要额外 API Key 给出执行前确认项。
## Running Rules
- 读取文件、写入/修改文件;会按任务需要访问外部网络;通常不需要额外 API Key。
- 先小样例验证,再放大到真实任务。
- 交付时同时给结果、检查口径和下一步迭代建议。 原文出现了 `/agents` 这类斜杠命令;如果你的 Agent 支持命令触发,优先用命令开场,再补充目标和边界。
告诉 Agent 目标文件或材料、期望结果、不可改范围、是否允许联网或执行命令。本 Skill 的权限画像是:读取文件、写入/修改文件。
先用一个小任务确认它会围绕“Documentation / Capabilities / FIRST: Verify Installation”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
检查最终产物是否包含明确结果、必要证据和下一步动作;如果输出泛泛而谈,就补充输入、边界和验收标准后重跑。
---
name: agents-sdk
description: Build AI agents on Cloudflare Workers using the Agents SDK. Load when creating stateful agents…
category: AI 智能
source: anomalyco/opencode
---
# agents-sdk
## 什么时候使用
- 把 AI / Agent方向的常用动作沉淀成 Agent 可调用的技能 适合处理AI Agent、提示词、模型评估与自动化推理,核心价值是把输入、判断、执行、验证和交付边界固定下来,避免 Agent 泛泛回答。 把任务拆成可执行、可检查…
- 面向提示词、Agent 工作流、模型评估或自动化推理,优先处理能明确输入、步骤和验收标准的工作。
## 需要提供什么
- 目标材料、目录范围、期望结果和不可改动内容。
- 是否允许联网、执行命令、读写文件或调用外部服务。
## 执行规则
- 围绕「Documentation / Capabilities / FIRST: Verify Installation」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件;会按任务需要访问外部网络;通常不需要额外 API Key。
- 先跑小样例,确认结果可检查后再扩大任务范围。
## 输出要求
- 给出最终产物、关键证据、验证方式和下一步动作。
- 信息不足时标记 unknown,不编造命令、平台或依赖。 作者原文负责流程事实;仓库文件负责来源和命令;流狐只补充适用场景、限制和质量判断。
skill "agents-sdk" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Documentation / Capabilities / FIRST: Verify Installation
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> 无特殊运行时 | 读取文件、写入/修改文件 | 会按任务需要访问外部网络
安全层 -> 通常不需要额外 API Key + 小任务验证 + diff / 日志复核
输出层 -> 可复制结果 + 检查清单 + 下一步迭代
} 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 |
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 -
AIChatAgentwith resumable streams - React hooks -
useAgent,useAgentChatfor 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)
先判断是否适合
作者设计意图
作者的方法与取舍
边界和复核