Events & event log

Every meaningful runtime moment in an OpenExpertise run fires an event. Events are:

• Emitted via EventBus.emit() from the scheduler, dispatchers, and StateStore.
• Subscribed by any number of listeners — pino for stdout logging, JsonlEventSink for the durable log, the TUI Dashboard for live render.
• Stored as one JSON object per line in .openexpertise/runs/<run-id>.jsonl.

The event types

type RunEvent =
  | { type: 'run.started'; run_id; ts; args? }
  | { type: 'run.finished'; run_id; ts; status: 'success' | 'failed' | 'partial' }
  | { type: 'node.ready'; run_id; node_id; ts; phase? }
  | { type: 'node.started'; run_id; node_id; ts; phase? }
  | { type: 'node.finished'; run_id; node_id; ts; phase?; metrics? }
  | { type: 'node.failed'; run_id; node_id; ts; phase?; error: string }
  | { type: 'node.skipped'; run_id; node_id; ts; phase?; reason: string }
  | { type: 'state.write'; run_id; node_id; field; ts }
  | { type: 'node.tokens'; run_id; node_id; ts; input_tokens; output_tokens; model? }
  | { type: 'node.activity'; run_id; node_id; ts; activity: string }

Every event has type and ts. Every node-scoped event has node_id. The schema is exhaustive — adding a new event type is a deliberate change to packages/core/src/events/bus.ts.

Where each event comes from

Event	Emitter
run.started	runExperience() before the scheduler runs
run.finished	runExperience() after the scheduler returns
node.ready	Scheduler when all predecessors are done
node.started	Scheduler before invoking a dispatcher
node.finished	Scheduler after a successful dispatcher run; includes metrics if returned
node.failed	Scheduler when a dispatcher throws (and on_error doesn't recover)
node.skipped	Scheduler when a predecessor failed/skipped, or when: evaluated false
state.write	StateStore on every successful write to a field
node.activity	LLM-touching dispatchers (agent, skill, cli-agent) at activity transitions
node.tokens	Agent + skill dispatchers after each LLM call, using result.usage

Reading the log back

The JSONL file is one event per line. Order is write order, which with the parallel scheduler can be non-chronological. oe inspect sorts by ts before rendering:

oe inspect r-abc123 --experience examples/review-branch

Output (sorted by ts ascending):

INFO: run.started     run_id=r-abc123 args={pr_id:"PR-1"}
INFO: node.ready      node_id=fetch_diff
INFO: node.started    node_id=fetch_diff
INFO: node.activity   node_id=fetch_diff activity="reading fixture"
INFO: state.write     node_id=fetch_diff field=diff
INFO: node.finished   node_id=fetch_diff
INFO: node.ready      node_id=seed_dimensions
INFO: node.started    node_id=seed_dimensions
INFO: state.write     node_id=seed_dimensions field=dimensions
INFO: node.finished   node_id=seed_dimensions
INFO: node.activity   node_id=bug_review activity="calling claude-sonnet-4-6"
INFO: node.tokens     node_id=bug_review input_tokens=1240 output_tokens=187
INFO: node.activity   node_id=bug_review activity="validating structured output"
INFO: state.write     node_id=bug_review field=findings
INFO: node.finished   node_id=bug_review
... etc ...
INFO: run.finished    status=success

Pipe to jq or grep for analysis:

cat .openexpertise/runs/r-abc123.jsonl | jq -c 'select(.type=="state.write")'
# → every state-mutation event

Why JSONL?

• One line = one event. Append-only writes are atomic at the OS level.
• Trivially grep-able, jq-able, awk-able.
• The event log survives crashes — JsonlEventSink uses synchronous appendFileSync for crash-safety.
• Replayable — you can deserialize and re-render any past run.

Subscribing programmatically

import { EventBus, runExperience } from '@openexpertise/core'

const events = new EventBus()

events.subscribe((event) => {
  if (event.type === 'node.tokens') {
    metrics.incrementCounter('tokens_in', event.input_tokens)
    metrics.incrementCounter('tokens_out', event.output_tokens)
  }
  if (event.type === 'node.failed') {
    pagerDuty.alert({ runId: event.run_id, nodeId: event.node_id, error: event.error })
  }
})

await runExperience({ ..., events })

The bus is in-process pub-sub. Any number of subscribers can attach; errors in one don't abort the run.

Custom event subscribers

A subscriber is just a function. Some useful ones:

• Prometheus metrics — bump counters on node.tokens and gauges on node.finished.metrics.cost_usd.
• PagerDuty — alert on node.failed.
• Audit log — write state.write events to an immutable external store.
• Cost tracker — sum node.tokens across runs to compute provider spend.

None of these are built into OpenExpertise V1 — they're three to ten lines of integration each.

What's NOT an event

Things the runtime does not emit:

• Per-byte LLM token output. No streaming. If you want token-by-token rendering, you need a streaming LLM client (not in V1).
• Tool internals. When a tool runs fetch() or queries a database, no event fires. Tool implementations are your code; instrument them yourself if you need it.
• Scheduler internal state. "How many nodes are in the ready queue right now?" — not exposed.

→ Continue with Scheduler.