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Events are signals from your application that trigger rule evaluation. You send events via the API, and Scrip evaluates all matching rules against the participant’s current state. Events can also come from automations, which generate events on a schedule or in response to participant state changes.

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Sending an Event

curl -X POST https://api.scrip.dev/v1/events \
  -H "Authorization: Bearer $SCRIP_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "program_id": "program-uuid",
    "external_id": "user_123",
    "idempotency_key": "order-456-completed",
    "event_timestamp": "2025-01-15T10:30:00Z",
    "event_data": {
      "type": "purchase",
      "amount": 99.50,
      "category": "electronics"
    }
  }'
FieldRequiredDescription
program_idYesWhich program’s rules should evaluate this event
external_idOne of external_id or participant_idYour application’s user ID
participant_idOne of external_id or participant_idScrip’s internal participant UUID
recipient_idNoRoute rewards to a different participant by Scrip UUID (e.g., gifting). Mutually exclusive with recipient_external_id.
recipient_external_idNoRoute rewards to a different participant by your external ID. Mutually exclusive with recipient_id.
idempotency_keyYesUnique key per program for exactly-once processing (1-255 characters)
event_timestampYesWhen the event occurred in your system (RFC 3339)
event_dataYesJSON object available to rules as event.* in CEL

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Timestamps

Every event carries two timestamps:
TimestampSet byPurpose
event_timestampYou, at ingestionWhen the event occurred in your system
created_atScrip, on receiptWhen Scrip received and stored the event
These serve different roles:
  • event_timestamp is the logical clock. It becomes the now variable in CEL expressions, so rule conditions that compare against time use the event’s occurrence time, not the current time. This keeps evaluation deterministic across retries and reprocessing.
  • created_at is the ingestion clock. The from and to query parameters on list endpoints filter on created_at, not event_timestamp. This makes incremental polling reliable: you can track “give me everything since my last sync” without missing late-arriving events. To filter by when events actually occurred, use the event_from and event_to parameters instead. Both pairs can be used simultaneously (AND semantics).
Because event_timestamp is customer-supplied, it can differ from created_at. A batch import might backdate events to last month, or clock skew might push timestamps slightly into the future. Rules evaluate against the current rule definitions regardless of event_timestamp. A backdated event runs against today’s rule definitions, but active_from / active_to windows are checked against the event’s event_timestamp, so a backdated event inside a past window still fires time-windowed rules. See Time-Windowed Rules.

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Processing Pipeline

Events are processed asynchronously. The API confirms receipt, not validity. Business validation (program existence and status, participant resolution) and rule evaluation happen in the background. Existing participants are automatically enrolled in the target program if not already members; see Programs: Enrollment for enrollment behavior and the on_unknown_participant setting. Validation errors surface via event.failed webhooks. 
POST /v1/events → 202 Accepted (queued for async validation)
                       ↓
               Worker picks up event
                       ↓
               Validation + rules evaluated against participant state
                       ↓
               Event transitions to COMPLETED or FAILED
When a worker picks up an event, it loads the program’s active rules and assembles the CEL context: the participant’s current state (tags, counters, attributes, tiers), program state, and group memberships. It then evaluates each rule’s condition against this context. Actions from matching rules execute within the same transaction. This context is a single event-start snapshot. All rule conditions for that event evaluate against the same snapshot. Actions from earlier matching rules do not change what later rule conditions see. See State Snapshot Evaluation Behavior for the implications and patterns. The rule definitions themselves are also read at processing time, not at ingestion. If you update a rule while events are queued, only events not yet processed use the new definition. A batch that spans the change can split across both versions. See Updating rules under live traffic for the full contract and how to reconcile which version applied. To check processing status: 
GET /v1/events/{id}
The response includes the event status, rule evaluations that occurred, and error details if processing failed.
Read-after-write visibility: the ID returned by the 202 is durable, but in queue-based ingestion mode the event may briefly 404 on both GET /v1/events/{id} and GET /v1/events/by-key (typically well under a second) until the async consumer materializes it. Poll until the ID resolves. Every accepted submission eventually becomes readable: either as a processed event or as status FAILED with an error_code if it was rejected asynchronously.
For a deeper view, use the impact endpoint to see everything an event caused: journal entries with postings, state changes, and per-entity balance impact. 
GET /v1/events/{id}/impact

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Event Lifecycle

StatusMeaning
PENDINGReceived, waiting for processing
PROCESSINGWorker is evaluating rules
COMPLETEDAll matching rules evaluated and their allowed actions executed
FAILEDValidation failed (invalid or inactive program, suspended or closed participant) or a rule action was blocked
RECEIVEDLegacy status on historical rows; new events enter at PENDING. Still accepted as a filter value.
Events whose resolved actor or recipient is SUSPENDED or CLOSED are rejected at the ingestion boundary, before any rule runs: 422 with code participant_suspended or participant_closed when identities resolve synchronously, or a terminal FAILED event with the same error_code in queue-based mode. See Participants: How this affects events.
Failed events carry a machine-readable error_code (when the failure has a classified code, such as participant_suspended or program_inactive) on the event resource and the event.failed webhook payload, so you can branch on failure type without string-matching the error message. If you have webhook endpoints configured, Scrip sends event.completed or event.failed notifications when processing finishes. This lets your application react to processing results without polling. Transient failures (infrastructure errors, timeouts) retry automatically with exponential backoff (2s, 4s, 8s, 16s, 32s), up to 5 retries. Validation failures are terminal; fix the cause and retry manually: 
POST /v1/events/{id}/retry
Manual retry resets the retry count and returns the event to PENDING for a fresh set of attempts.

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Idempotency

The idempotency_key ensures exactly-once processing per program. If you send the same program_id + idempotency_key combination more than once, the duplicate is ignored and the original event is returned. This applies regardless of whether the payload differs. If a network timeout occurs, re-send the same request. The duplicate is safely deduplicated. Treat idempotency keys as unique identifiers per intent. If the payload needs to change (e.g., correcting an amount), use a new key.
Use meaningful, deterministic idempotency keys like order-12345-completed or referral-user456-signup. Avoid random UUIDs, which defeat the purpose of deduplication.
You can also look up an event by its key: 
GET /v1/events/by-key?program_id={program_id}&idempotency_key=order-12345-completed

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Event Data Design

The event_data payload becomes the event variable in CEL expressions. Design it with rules in mind: 
{
  "type": "purchase",
  "amount": 49.99,
  "category": "electronics",
  "store_id": "store-west-01",
  "order_id": "order-789"
}
TipRationale
Include a consistent type fieldClean rule filtering: event.type == "purchase"
Keep amounts as numbersAvoids double() casting in rules
Use snake_case for field namesConsistency with the API
Include context for debuggingstore_id, order_id help troubleshoot
Rules reference event_data fields directly as event.amount, event.category, etc. If a rule references a field that isn’t in the payload, the condition evaluates to false and the rule doesn’t match. Use has() for fields that only appear on some events. See CEL Expressions.

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Batch Ingestion

Send up to 100 events in a single request: 
POST /v1/events/batch
{
  "events": [
    {"program_id": "...", "external_id": "user_1", "idempotency_key": "evt-1", "event_timestamp": "...", "event_data": {"type": "purchase", "amount": 50}},
    {"program_id": "...", "external_id": "user_2", "idempotency_key": "evt-2", "event_timestamp": "...", "event_data": {"type": "purchase", "amount": 75}}
  ]
}
Each event is accepted, validated, and processed independently; a batch is never all-or-nothing. The 202 response reports per-event outcomes: each entry in results is either accepted (with the full event object) or error (with an error_code and message). Valid events proceed even when siblings fail. A 400 is returned only when the envelope itself is malformed (zero events, more than 100, or unparseable JSON). Business validation errors surface later via event.failed webhooks.

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Event Routing

By default, rule actions apply to the event’s participant. To credit a different participant, include their identifier in event_data and reference it in the rule action’s target: 
{
  "program_id": "...",
  "external_id": "user_123",
  "idempotency_key": "referral-user123-signup",
  "event_timestamp": "2025-01-15T10:30:00Z",
  "event_data": {
    "type": "referral",
    "referrer_id": "user_456"
  }
}

{
  "name": "Referral Bonus",
  "condition": "event.type == 'referral'",
  "actions": [
    {
      "type": "CREDIT",
      "asset_id": "...",
      "amount": "50",
      "target": {"external_id": "${{ event.referrer_id }}"}
    }
  ]
}
The target field’s external_id accepts a CEL expression that resolves to a participant’s external ID. You can also use participant_id to resolve by Scrip UUID. The target participant must exist (they are automatically enrolled if not already a member of the program). Rules always evaluate conditions against the event’s participant (user_123). Only the action’s credit is routed to the target. See Rule Actions for more on static and dynamic targeting.