Events

This page explains the lifecycle events emitted by scopes, tools, LLM calls, middleware, and subscribers.

What Events Represent

Events are the runtime record of what happened. NeMo Relay uses Agent Trajectory Observability Format (ATOF) 0.1 as the canonical event format for scopes, managed execution helpers, manual lifecycle APIs, subscribers, and exporters.

Event Kinds

ATOF has two event kinds.

scope

Emitted when lifecycle work starts or ends. scope_category is start or end, and category identifies the kind of work, such as agent, function, tool, llm, retriever, embedder, reranker, guardrail, evaluator, custom, or unknown.

mark

Emitted for named runtime checkpoints that are not full start/end lifecycle pairs.

The coding-agent CLI emits one session.start mark when a session lifecycle begins. Its metadata includes the logical harness session_id, the Relay-owned session_instance_id, and any configured session metadata such as user_id. The mark does not copy the native startup-hook payload or force a turn scope to open.

Shared Envelope

Every event carries a shared envelope:

• kind
• atof_version
• uuid
• parent_uuid
• timestamp
• name
• data
• data_schema
• metadata

Scope events add scope_category, category, attributes, and optional category_profile. Mark events can optionally carry category and category_profile, though the current public mark helpers emit generic marks without those optional category fields.

Runtime helpers assign timestamps automatically by default. Manual lifecycle helpers for scopes, marks, tool calls, and LLM calls also accept an explicit timestamp for integrations that are replaying events or mirroring an upstream framework clock. Use explicit timestamps only when the caller owns a reliable event time; otherwise prefer the runtime-generated timestamp.

Native Rust, Python, Node.js, and FFI event-producing APIs construct canonical events synchronously, enqueue subscriber delivery, and return without waiting for subscriber callbacks, exporter work, file writes, or tracing processors. Use the binding flush API when a test or shutdown path must wait for queued subscriber work.

Semantic Meaning

These sections describe how event shapes and relationships should be interpreted by consumers.

Start and End Pairing

Start and end scope events for the same lifecycle pair by UUID. That pairing lets subscribers compute durations, reconstruct call boundaries, and preserve nesting in downstream systems.

Input and Output Payloads

ATOF uses one data field. For scope events, data is the semantic input on scope_category == "start" and the semantic output on scope_category == "end".

LLM start annotations use freshness state owned by the nearest agent scope:

• Fresh history: An agent starts fresh when its scope opens and becomes fresh again after a compaction mark. The first subsequent LLM start retains the complete available request history and consumes the fresh state.
• Stale history: After that first start, later LLM starts retain all system instructions, the latest user message, and every following assistant or tool message. If the history has no user message, the annotation retains system instructions and the final non-system message.
• Scope ownership: Nested agents track freshness independently. The implicit root is the freshness owner for work outside an explicit agent. Non-agent scopes inherit their nearest agent’s state instead of starting a new budget.
• Codec projection: When a request codec supplies an annotation, Relay applies the same history projection to the event’s provider-shaped input. If that event-only encode fails, Relay retains the complete event input and annotation. The request used for provider execution remains unchanged.
• Concurrency: Concurrent starts have no guaranteed emission order, but exactly one consumes a fresh state. Events are independent observations, not a replayable history stream.

Category Profiles

Category-specific fields live under category_profile. NeMo Relay uses model_name for LLM events, tool_call_id for tool events, and subtype for custom-category events. LLM codec annotations, when present, are serialized under category_profile.annotated_request on LLM start events and category_profile.annotated_response on LLM end events. Unknown profile fields are preserved so newer producers can interoperate with older consumers.

Annotated Request and Response Data

LLM codecs can enrich LLM events with annotated request and response data. These annotations are part of the canonical event JSON under category_profile when they are present, so ATOF JSONL export and in-process subscriber JSON expose the same payload shape. Request annotations use the owning agent’s freshness state.

Event Contract Boundary

The event is the canonical envelope and handoff point for subscribers and exporters. Consumers should prefer typed event fields, binding helpers, and annotated request or response data before falling back to raw payload re-reading.

Before that handoff, event sanitizers can replace data, category_profile, and metadata. The runtime keeps identity, lifecycle, category, timestamp, and parent fields immutable. Refer to Event Sanitizers for registration levels and ordering.

Events preserve runtime facts. They do not decide which scope owns a call, how replay or cost policy is applied, how redaction policy is configured, how streams are blocked, or how exporter-specific semantic projection works. Those decisions stay in the session, codec, plugin, guardrail, or exporter layer that owns them.

Automatic Skill-Load Marks

NeMo Relay automatically records an on-demand skill-load attempt when an instrumented tool explicitly names a skill or requests a complete SKILL.md read. The following payload excerpt shows the stable skill-load fields. Standard fields from the shared envelope, such as atof_version, uuid, parent_uuid, and timestamp, are omitted.

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{
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  "kind": "mark",
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  "name": "skill.load",
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  "data": {"skill_name": "review"},
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  "metadata": {
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    "skill_load_source": "structured_read",
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    "tool_name": "read_file"
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  }
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}

Relay uses these skill_load_source values:

For reader detections, the path must end in SKILL.md; the skill name is its immediate parent directory. A nonzero structured offset, any structured limit or range control, shell pipelines, redirections, compound commands, and range-limited shell readers do not count. An explicit structured offset of 0 still represents a complete read. Relay omits the full path and shell command from the mark.

The mark has these lifecycle semantics:

• Relay emits it immediately after the tool-start event and before execution, with the tool span as its parent.
• It records an eager load attempt and remains present if the tool later fails.
• A blocked call that never starts does not emit the mark.
• Relay emits each skill once per tool call. A later call that attempts the same load emits another mark.

Claude Code Skill, Codex complete-reader shell calls, Hermes skill_view, and tool calls made through the Rust, Python, Node.js, Go/FFI, LangChain, LangGraph, and Deep Agents paths use this observed contract. The existing Deep Agents DeepAgents Skills Configured mark remains a separate configuration summary; it does not mean that a skill body was loaded.

Claude Code exposes slash-command expansion without saying whether the command came from a skill or a legacy command. For a nonempty slash-command expansion, Relay emits skill.load.inferred with data.skill_name, metadata.skill_load_source = "prompt_expansion", and metadata.inferred = true. Relay also includes metadata.command_source when Claude Code provides it. Keep inferred and observed counts separate.

Exporters handle the mark as follows:

• ATOF preserves the canonical mark event.
• ATIF omits marks because it models trajectory steps rather than independent point-in-time events.
• OpenTelemetry and OpenInference apply their configured mark_projection to parented marks.

How Events Are Produced

Scope APIs emit scope start and end events and can also emit named mark events. Managed tool and LLM helpers emit scope events with category set to tool or llm. Conditional-execution rejections and explicit mark points let the runtime record important state transitions even when there is no full nested callback to wrap. Subscriber delivery is downstream from event construction and does not block the emitting call on native bindings.

ATOF export writes this raw canonical event stream. ATIF, OpenTelemetry, and OpenInference are downstream projections over the same events.