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Event Model

OpenBox receives both governed lifecycle events and operational telemetry from the OpenBox: Agent node. Understanding that model is necessary for writing policy, configuring guardrails, and interpreting the dashboard correctly.

Top-Level Event Types​

Event typeEmitted byPrimary use
WorkflowStartedbeforeAgentStart-of-run governance
WorkflowCompletedafterAgentFinal outcome (completed or failed) and summary telemetry
SignalReceivedbeforeAgent, before the model runsPrompt-level context and auditability
LLMStartedwrapModelCall, before the Chat Model is invokedInput-time model governance and prompt guardrails
LLMCompletedwrapModelCall, after the Chat Model returnsOutput-time model governance, token usage, and response metadata
ToolStartedwrapToolCall, before the Tool sub-node executesInput-time tool governance and approvals
ToolCompletedwrapToolCall, after the Tool sub-node executesOutput-time tool governance and tool result telemetry

On the wire, LLMStarted/LLMCompleted and ToolStarted/ToolCompleted are sent to OpenBox Core as ActivityStarted/ActivityCompleted — the original LangChain-style name is preserved as metadata.sdk_event_type so the dashboard can still distinguish LLM spans from tool spans.

Business Events Versus Internal Telemetry​

Business events are the node's four lifecycle stages:

  • agent run start and completion
  • model call start and completion
  • tool call start and completion

These are not separate business events:

  • internal HTTP telemetry (including the HTTP call to the model provider itself)
  • internal database telemetry

Those appear as operational spans associated with the active model call, tool call, or agent run.

How Agent Runs Appear​

Each OpenBox: Agent node execution creates a fresh run identity in beforeAgent. The workflow type sent to OpenBox is n8n.Agent.<node display name> unless you configure the node's display name differently — see Configuration.

Important implications:

  • A single node execution can appear as a workflow run in OpenBox.
  • The initiating prompt is emitted as SignalReceived(user_prompt).
  • Model work is represented by LLMStarted and LLMCompleted, not as a tool activity.
  • If the item has a string sessionId field, it is used as the OpenBox session identifier for that item.

Model Payload Shape Guidance​

LLMStarted​

Common fields:

  • prompt — the last human message, not the full concatenated chat history
  • activity_input[0].prompt
  • activity_type = "llm_call"

LLMCompleted​

Common fields:

  • completion
  • llm_model
  • input_tokens, output_tokens, total_tokens
  • has_tool_calls

Tool Payload Shape Guidance​

ToolStarted​

Common fields:

  • tool_name
  • tool_type — always absent in the current n8n node; there is no tool_type_map equivalent in the UI yet
  • activity_type
  • activity_input

ToolCompleted​

Common fields:

  • tool_name
  • activity_output
  • status (completed or failed)
  • duration_ms

Typical Event Sequences​

Agent Run With A Model Call​

SignalReceived(user_prompt)
-> WorkflowStarted
-> LLMStarted
-> zero or more telemetry spans during model execution
-> LLMCompleted
-> WorkflowCompleted

Agent Run With A Tool Call​

SignalReceived(user_prompt)
-> WorkflowStarted
-> LLMStarted -> LLMCompleted (model decides to call a tool)
-> ToolStarted
-> zero or more telemetry spans during tool execution
-> ToolCompleted
-> LLMStarted -> LLMCompleted (model reads the tool result)
-> WorkflowCompleted

Output-Side Redaction​

If WorkflowCompleted's guardrail result redacts the activity output, the node overwrites the node's returned output field with the redacted text. The unredacted response was already written to Memory, if a Memory sub-node is connected — redaction is applied to the OpenBox-facing node output only.

Model Usage And Tool Health In The UI​

  • Model and token usage come from LLMCompleted metadata when the connected Chat Model returns it.
  • Tool health populates for agents that actually execute tools.
  • An agent run that only generates text without tools may show model usage but no tool health.

Policy And Guardrail Guidance​

Recommended approach:

  1. Use LLMStarted for prompt-side model governance.
  2. Use LLMCompleted for response-side model governance.
  3. Use ToolStarted for tool-input guardrails and approval policies.
  4. Use ToolCompleted for tool-output guardrails and result review.
  5. Treat HTTP and database telemetry as internal by default.