Pre-release Harn is pre-1.0 — the language, standard library, and CLI may change between releases. See the release notes

Trigger stdlib

The trigger stdlib exposes the live runtime registry to Harn scripts. Use it to inspect installed bindings, register new bindings at runtime, fire synthetic events for tests/manual invocations, replay a recorded event by id, and inspect the current dead-letter queue (DLQ).

Import the shared types from std/triggers when you want typed handles and payloads:

import "std/triggers"

Builtins

trigger_list()

Return the current live registry snapshot as list<TriggerBinding>.

Each binding includes:

  • id
  • version
  • source ("manifest" or "dynamic")
  • kind
  • provider
  • autonomy_tier
  • handler_kind
  • state
  • metrics

metrics is a typed TriggerMetrics record with counters for received, dispatched, failed, dlq, in_flight, and the cost snapshot fields.

trigger_register(config)

Register a trigger dynamically and return its TriggerHandle.

TriggerConfig uses the same broad shape as manifest-loaded bindings:

  • id
  • kind
  • provider
  • autonomy_tier
  • handler
  • when
  • when_budget
  • retry
  • match or events
  • dedupe_key
  • filter
  • allow_cleartext
  • budget
  • manifest_path
  • package_name

Dynamic trigger_register(...) currently supports the legacy budget fields but does not yet accept manifest-only flow-control tables such as concurrency, throttle, rate_limit, debounce, singleton, batch, or keyed priority.

The runtime currently accepts two handler forms:

  • Local Harn closures / function references
  • Remote URI strings with a2a://... or worker://...

Local handler and predicate entrypoints receive (harness: Harness, event: TriggerEvent). Predicates may therefore perform governed classification, including model calls, before dispatch. Inside either boundary, ordinary helpers should accept the smallest coherent capability interface they need rather than inheriting the root Harness.

allow_cleartext is optional and only applies to a2a://... handlers. Set it to true when you intentionally want HTTP A2A discovery / dispatch, for example when talking to a local harn serve process during development.

retry is optional. The current stdlib surface accepts:

  • {max: N, backoff: "svix"}
  • {max: N, backoff: "immediate"}

Example:

import "std/triggers"

fn handle_issue(harness: Harness, event: TriggerEvent) -> dict {
  return {kind: event.kind, provider: event.provider}
}

const handle: TriggerHandle = trigger_register({
  id: "github-new-issue",
  kind: "issue.opened",
  provider: "github",
  autonomy_tier: "act_with_approval",
  handler: handle_issue,
  allow_cleartext: nil,
  when: nil,
  when_budget: nil,
  match: {events: ["issue.opened"]},
  events: nil,
  dedupe_key: nil,
  filter: nil,
  budget: nil,
  manifest_path: nil,
  package_name: nil,
})

trigger_fire(handle, event)

Fire a synthetic TriggerEvent into a binding and return a DispatchHandle.

The builtin accepts either:

  • A TriggerHandle / TriggerBinding dict
  • A plain trigger id string

If the event dict omits low-level envelope fields such as id, received_at, trace_id, or provider_payload, the runtime fills them with synthetic defaults.

Current behavior:

  • Execution routes through the trigger dispatcher, so local handlers inherit dispatcher retries, lifecycle events, action-graph updates, and DLQ moves.
  • when predicates execute before the handler and can still short-circuit a dispatch.
  • when_budget accepts {max_cost_usd, tokens_max, timeout} and applies fail-closed per-predicate LLM cost governance.
  • When a manifest-installed binding uses batch = { ... }, the selected leader event carries the coalesced member list in event.batch.
  • a2a://... handlers return either the inline remote result or a pending task handle, depending on the peer response.
  • worker://... handlers return an enqueue receipt in DispatchHandle.result with {queue, job_event_id, response_topic}.

trigger_replay(event_id)

Replay a previously recorded event from the EventLog by id and return a DispatchHandle.

Current replay behavior:

  • Fetch the prior event from the triggers.events topic
  • Re-dispatch it through the trigger dispatcher using the recorded binding
  • Preserve replay_of_event_id on the returned DispatchHandle
  • Resolve the pending stdlib DLQ entry when a replay succeeds

trigger_replay(...) is still not the full deterministic T-14 replay engine. It replays the recorded trigger event through the current dispatcher/runtime state rather than a sandboxed drift-detecting environment.

trigger_inspect_dlq()

Return the current DLQ snapshot as list<DlqEntry>.

Each DlqEntry includes:

  • The failed event
  • Trigger identity (binding_id, binding_version)
  • Current state
  • Latest error
  • Derived error_class (provider_5xx, predicate_panic, handler_panic, handler_timeout, auth_failed, budget_exhausted, or unknown)
  • retry_history

retry_history records every DLQ attempt, including replay attempts.

trigger_inspect_lifecycle(kind?)

Return the trigger lifecycle stream as a list of {kind, headers, payload} records. Pass a kind such as predicate.evaluated, predicate.budget_exceeded, or DispatchStarted to filter on the runtime side.

trigger_inspect_action_graph(trace_id?)

Return streamed observability.action_graph records as a list of {kind, headers, payload} records. Pass a trace_id to filter the stream to one trigger delivery and its downstream predicate, dispatch, retry, worker, A2A, and DLQ nodes.

harness.runtime.handler_context()

Return the current dispatch context as HandlerContext | nil.

Inside a trigger handler, the returned record includes:

  • agent
  • action
  • trace_id
  • replay_of_event_id
  • autonomy_tier
  • trigger_event

Outside trigger dispatch, the method returns nil.

Stream helpers

std/triggers includes small declarative helpers for stream handlers:

  • stream_fork(source, branches) returns a StreamForkPlan
  • stream_join(source, join?) returns a StreamJoinPlan
  • window_by(events, window) returns a StreamWindowPlan
  • llm_classify(input, labels, options?) returns a StreamLlmClassifyPlan

These helpers do not start broker consumers by themselves. They give handlers a typed, serializable plan shape for fan-out/fan-in, manifest-aligned windowing, and cached classifier steps.

import "std/triggers"

pub fn on_quotes(harness: Harness, event: TriggerEvent) -> dict {
  const forked = stream_fork([event.provider_payload.raw], ["risk", "ledger"])
  const windowed = window_by(
    [event.provider_payload.raw],
    {mode: "sliding", key: "event.provider_payload.key", size: "5m", every: "1m", gap: nil, max_items: 500},
  )
  const classified = llm_classify(event.provider_payload.raw, ["ignore", "review"], {cache: "quotes:v1"})
  return {forked: forked, windowed: windowed, classified: classified}
}

trust_record(agent, action, approver, outcome, tier)

Append a manual OpenTrustGraph TrustRecord to the trust graph. Scripts usually rely on the dispatcher's automatic end-of-handler records, but this builtin is available for control-plane events such as promotions, demotions, or manual audit entries. The returned record includes chain_index, previous_hash, and entry_hash, and the runtime also mirrors a compact projection to trust_graph.records.

trust_graph_record(decision)

Append a decision dict to the trust graph and return its TrustEntryId (record_id). The dict accepts agent/actor_id, action, approver, outcome, trace_id, autonomy_tier/autonomy_tier_at_time (or tier), evidence_refs, cost_usd, and metadata.

trust_graph_query(agent, action)

Return a TrustScore for an agent and optional action. Scores include outcome counts, success rate, latest outcome, effective autonomy tier, and a capability policy that handlers can use as a gate.

trust_graph_policy_for(agent)

Return only the derived CapabilityPolicy for an agent.

trust_graph_verify_chain()

Verify the active trust graph hash chain and return a report with verified, root_hash, broken_at_event_id, and errors.

trust_query(filters)

Query historical trust records from Harn code.

Supported filter keys:

  • agent
  • action
  • since
  • until
  • tier
  • outcome
  • limit
  • grouped_by_trace

limit keeps only the newest N matching records. When grouped_by_trace is true, the builtin returns list<{trace_id, records}> trace buckets instead of the default flat list<TrustRecord>.

For new code, prefer import "std/trust" and call query(...) or trust.query(...) to receive the compact issue-facing TrustGraphRecord shape with actor_id, evidence_refs, and autonomy_tier_at_time.

Example

import "std/triggers"

fn fail_handler(harness: Harness, event: TriggerEvent) -> any {
  throw("manual failure: " + event.kind)
}

const handle = trigger_register({
  id: "manual-dlq",
  kind: "issue.opened",
  provider: "github",
  handler: fail_handler,
  when: nil,
  when_budget: nil,
  retry: {max: 1, backoff: "immediate"},
  match: nil,
  events: ["issue.opened"],
  dedupe_key: nil,
  filter: nil,
  budget: nil,
  manifest_path: nil,
  package_name: nil,
})

const fired = trigger_fire(handle, {provider: "github", kind: "issue.opened"})
const dlq = trigger_inspect_dlq().filter({ entry -> entry.binding_id == handle.id })
const replay = trigger_replay(fired.event_id)

harness.stdio.log(fired.status)                  // "dlq"
harness.stdio.log(len(dlq[0].retry_history))     // 1
harness.stdio.log(replay.replay_of_event_id)     // original event id

Notes

  • Dynamic registrations are runtime-local. trigger_register(...) updates the live registry in the current process; it does not rewrite harn.toml.
  • a2a://... bindings default to HTTPS-only. Use allow_cleartext: true only for intentional local or otherwise trusted HTTP peers.
  • TriggerConfig.autonomy_tier defaults to act_auto when omitted.
  • trigger_fire(...) and trigger_replay(...) need an active EventLog to persist triggers.events and triggers.dlq. If the runtime did not already install one, the stdlib wrapper falls back to an in-memory log for the current thread.
  • Predicate replay is deterministic for harness.llm.call(...): cached predicate responses are reused from the request cache plus the per-event trigger.inbox record rather than calling the live provider again.
  • Every terminal dispatch appends one TrustRecord to trust.graph plus the per-agent topic trust.graph.<agent_id>.
  • When workflow_execute(...) runs inside a replayed trigger dispatch, the runtime carries the replay pointer into run metadata so derived observability can render a replay_chain edge back to the original event.
Previous
Triggers
Next
Trigger manifests
Edit this page on GitHub