Agent助手
- 作者仓库星标 77,599
- 作者更新于 实时读取
- 作者仓库 lobehub
- 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
- @lobehub · 未声明 license
- Token 消耗评级
- 低消耗
- 接入复杂程度
- 需简单配置
- 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
- Node.js
- 文件与系统权限
-
- 只读
- 允许写入 / 修改
- Shell 执行
- 网络行为
- 仅限本地
- 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: agent-signal
description: Build or extend LobeHub Agent Signal pipelines for background or quiet agent work driven by even…
category: AI 智能
runtime: Node.js
---
# agent-signal 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“Start Here / Use The Right Entry Point / Core Model”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“Start Here / Use The Right Entry Point / Core Model”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、执行终端命令、主要在本地完成、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、执行终端命令;主要在本地完成;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。 先确认触发方式
原文没有稳定的斜杠命令要求。安装验证后通常全局生效,直接在对话里点名这个 Skill 并描述任务即可。
给清楚输入和边界
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、执行终端命令。
小样例验证后再放大
先用一个小任务确认它会围绕“Start Here / Use The Right Entry Point / Core Model”工作;涉及文件或命令时,先看 diff、日志、预览或测试结果。
复核后再交付
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: agent-signal
description: Build or extend LobeHub Agent Signal pipelines for background or quiet agent work driven by even…
category: AI 智能
source: lobehub/lobehub
---
# agent-signal
## 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「Start Here / Use The Right Entry Point / Core Model」组织步骤,不把推断写成作者事实。
- 读取文件、写入/修改文件、执行终端命令;主要在本地完成;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。 证据边界与执行链路
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 "agent-signal" {
输入层 -> 用户目标 + 目标文件 + 禁止范围 + 验收标准
上下文层 -> Start Here / Use The Right Entry Point / Core Model
规则层 -> SKILL.md 触发条件 / 执行顺序 / 输出格式
运行层 -> Node.js | 读取文件、写入/修改文件、执行终端命令 | 主要在本地完成
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
} Agent Signal
Use this skill to implement event-driven background work for agents without coupling the work to the foreground chat request.
Agent Signal has one consistent shape:
source event -> signal interpretation -> action execution -> built-in result signals
Start Here
- Read
references/architecture.mdto map the package boundary, runtime queue, scope model, and async workflow handoff. - Read
references/handlers.mdbefore writing any new policy, source handler, signal handler, or action handler. - Read
references/observability.mdwhen you need tracing, metrics, debugging, or workflow snapshot visibility.
Use The Right Entry Point
- Use
emitAgentSignalSourceEvent(...)when a server-owned producer should execute the pipeline immediately. - Use
executeAgentSignalSourceEvent(...)when a worker or controlled backend path already owns execution timing and may inject a runtime guard backend. - Use
enqueueAgentSignalSourceEvent(...)when the caller should return quickly and let Upstash Workflow process the event out-of-band. - Use
emitAgentSignalSourceEventWithStore(...)for isolated tests or evals that should avoid ambient Redis state.
Read:
src/server/services/agentSignal/index.tssrc/server/workflows/agentSignal/index.tssrc/server/workflows/agentSignal/run.ts
Core Model
source: A normalized fact that happened. Sources come from producers such as runtime lifecycle events, user messages, or bot ingress.signal: A semantic interpretation derived from one source or from another signal. Signals express meaning, routing, or policy state.action: A concrete side effect planned from one signal. Actions do the work.policy: An installable middleware bundle that registers source, signal, and action handlers.procedure: Not a distinct runtime node. Treat "procedure" as the end-to-end flow for one use case: ingress source, matching handlers, planned actions, execution result, and observability.
Keep the boundaries strict:
- Add a new
sourcewhen the outside world produced a new event. - Add a new
signalwhen the system needs a reusable semantic interpretation. - Add a new
actionwhen the runtime needs a concrete side effect. - Add or update a
policywhen you are wiring those pieces together.
Implementation Workflow
- Decide whether the use case is synchronous or quiet background work.
- Define or reuse a source type in
src/server/services/agentSignal/sourceTypes.ts. - Define or reuse signal and action types in
src/server/services/agentSignal/policies/types.ts. - Implement handlers with
defineSourceHandler,defineSignalHandler, ordefineActionHandler. - Bundle handlers with
defineAgentSignalHandlers(...). - Register the policy in
src/server/services/agentSignal/policies/index.tsand pass it into the runtime factory if needed. - Add or update ingress code that emits or enqueues the source event.
- Add observability and tests before considering the flow complete.
Default Reading Set
- Shared semantic core:
packages/agent-signal/src/index.tspackages/agent-signal/src/base/builders.tspackages/agent-signal/src/base/types.ts - Server-owned runtime and middleware:
src/server/services/agentSignal/runtime/AgentSignalRuntime.tssrc/server/services/agentSignal/runtime/AgentSignalScheduler.tssrc/server/services/agentSignal/runtime/middleware.tssrc/server/services/agentSignal/runtime/context.ts - Existing policy example:
src/server/services/agentSignal/policies/analyzeIntent/index.tssrc/server/services/agentSignal/policies/analyzeIntent/feedbackSatisfaction.tssrc/server/services/agentSignal/policies/analyzeIntent/feedbackDomain.tssrc/server/services/agentSignal/policies/analyzeIntent/feedbackAction.tssrc/server/services/agentSignal/policies/analyzeIntent/actions/userMemory.ts - Observability:
src/server/services/agentSignal/observability/projector.tssrc/server/services/agentSignal/observability/traceEvents.tspackages/observability-otel/src/modules/agent-signal/index.ts
Implementation Rules
- Reuse existing source, signal, and action types before adding new ones.
- Keep source handlers focused on interpretation and fan-out, not heavy side effects.
- Keep action handlers responsible for side effects, idempotency, and executor-style result reporting.
- Use stable ids and idempotency keys when the same source can arrive more than once.
- Preserve scope discipline. The runtime uses
scopeKeyto serialize related background work. - Prefer the dedicated shared package types and builders from
@lobechat/agent-signalfor normalized nodes and result contracts. - Add focused tests near the touched runtime, policy, or store module. Existing tests under
src/server/services/agentSignal/**/__tests__are the reference pattern.
References
- Architecture and boundaries:
references/architecture.md - Writing handlers and policies:
references/handlers.md - Observability, metrics, and debugging:
references/observability.md
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