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agent-signal

agent-signal

github.com/lobehubAgent workflows83.6k92 installsUpdated today
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About agent-signal

Agent Signal is a development skill for building event-driven background work in agent systems, separate from foreground chat requests. It explains how to route source events through interpretation and actions, with guidance on async execution, scope, completion receipts, tests, and observability.

Key features

  1. 01Models sources, signals, actions, and policies
  2. 02Explains synchronous and queued entry points
  3. 03Guides handler and policy implementation
  4. 04Covers scope and idempotency practices
  5. 05Documents tracing, metrics, and tests

Use cases

  1. 01Adding background work triggered by runtime events
  2. 02Routing user or bot events into agent actions
  3. 03Implementing durable self-iteration completion flows

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/lobehub/lobehub --skill agent-signal

After installing, type/agent-signalin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

agents/
openai.yaml
references/
architecture.md
handlers.md
observability.md

Details

From the project README

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 runtime shape:

source event -> signal interpretation -> action execution -> built-in result signals

Durable self-iteration work has one extra completion branch:

memory/skill action -> execAgent enqueue -> agent.execution.completed -> selfIteration receipt projection

Start Here

  1. Read references/architecture.md to map the package boundary, runtime queue, scope model, and async workflow handoff.
  2. Read references/handlers.md before writing any new policy, source handler, signal handler, or action handler.
  3. Read references/observability.md when 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:

  • apps/server/src/services/agentSignal/index.ts
  • apps/server/src/workflows/agentSignal/index.ts
  • apps/server/src/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 source when the outside world produced a new event.
  • Add a new signal when the system needs a reusable semantic interpretation.
  • Add a new action when the runtime needs a concrete side effect.
  • Add or update a policy when you are wiring those pieces together.

Implementation Workflow

  1. Decide whether the use case is synchronous or quiet background work.
  2. Define or reuse a source type in packages/agent-signal/src/source/sourceTypes.ts.
  3. Define or reuse signal and action types in apps/server/src/services/agentSignal/policies/types.ts.
  4. Implement handlers with defineSourceHandler, defineSignalHandler, or defineActionHandler.
  5. Add source normalization or hydration under apps/server/src/services/agentSignal/sources/** when the producer payload needs shaping.
  6. Bundle handlers with defineAgentSignalHandlers(...).
  7. Register the policy in apps/server/src/services/agentSignal/policies/index.ts and pass it into the runtime factory if needed.
  8. Add or update ingress code that emits or enqueues the source event.
  9. For async self-iteration writes, stamp an Agent Signal operation marker and project user-visible receipts from the completion path.
  10. Add observability and tests before considering the flow complete.

Default Reading Set

  • Shared semantic core: packages/agent-signal/src/index.ts packages/agent-signal/src/base/builders.ts packages/agent-signal/src/base/types.ts packages/agent-signal/src/source/sourceTypes.ts packages/agent-signal/src/source/sourceEvent.ts
  • Server-owned runtime and middleware: apps/server/src/services/agentSignal/runtime/AgentSignalRuntime.ts apps/server/src/services/agentSignal/runtime/AgentSignalScheduler.ts apps/server/src/services/agentSignal/runtime/middleware.ts apps/server/src/services/agentSignal/runtime/context.ts
  • Existing policy example: apps/server/src/services/agentSignal/policies/analyzeIntent/index.ts apps/server/src/services/agentSignal/policies/analyzeIntent/feedbackSatisfaction.ts apps/server/src/services/agentSignal/policies/analyzeIntent/feedbackDomain.ts apps/server/src/services/agentSignal/policies/analyzeIntent/feedbackAction.ts apps/server/src/services/agentSignal/policies/analyzeIntent/actions/userMemory.ts apps/server/src/services/agentSignal/policies/analyzeIntent/actions/skillManagement.ts apps/server/src/services/agentSignal/policies/analyzeIntent/completionSkillSynthesis.ts apps/server/src/services/agentSignal/policies/completionPolicy.ts apps/server/src/services/agentSignal/services/selfIteration/completion/buildSelfIterationReceipts.ts apps/server/src/services/agentSignal/services/selfIteration/completion/selfIterationCompletionHandler.ts
  • Observability: apps/server/src/services/agentSignal/observability/projector.ts apps/server/src/services/agentSignal/observability/traceEvents.ts packages/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. For memory/skill self-iteration actions, the side effect is enqueueing execAgent; the durable write and receipt projection happen after completion.
  • Use stable ids and idempotency keys when the same source can arrive more than once.
  • Preserve scope discipline. The runtime uses scopeKey to serialize related background work.
  • Prefer the dedicated shared package types and builders from @lobechat/agent-signal for normalized nodes and result contracts.
  • Do not project memory or skill receipts from the enqueue action. Use agent.execution.completed + selfIteration finalState via createSelfIterationCompletionHandler(...).
  • Add focused tests near the touched runtime, policy, or store module. Existing tests under apps/server/src/services/agentSignal/**/__test__ and **/__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

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