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Normalize every supported trigger at the workflow’s entry point: decode its documented wire format, map it into a canonical internal object, validate that object against the workflow contract, and send only the validated result to orchestration. Parsing makes input readable; it does not make it valid. The exact request envelope and field names depend on the workflow API.
Why normalize at workflow entry?
A workflow may be started by a direct API call, a webhook, or another trigger. Those sources can differ in content type, envelope, field names, and serialization. If each workflow step handles those differences, transport-specific conditionals spread into business logic and equivalent requests can produce inconsistent results.
Use one explicit boundary for each ingress path. It should translate that source’s request into a shared internal representation before the workflow’s business steps run. The RayLabs article on this topic describes a case where one path supplies an object and another a JSON-encoded string; treat that as an implementation scenario, not a general rule for direct workflow APIs. Confirm the actual runtime and endpoint contract rather than assuming either format.
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Document each supported source’s contract before writing normalization logic. Specify the content type, body or envelope shape, accepted and required fields, authentication or signature rules, and error behavior. Also decide how schema versions evolve, whether unknown keys are rejected, and whether defaults are safe and unambiguous. These policies belong to the specific endpoint; there is no universal workflow API field convention.
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For example, Runsight documents a direct invocation body containing only an inputs object and describes validation failures as HTTP 422. Those are Runsight-specific details, not general API requirements. Keep caller-controlled inputs distinct from server-owned run metadata. Runsight, for instance, describes server-authored source and branch metadata.
Normalize, then validate
- Retain the original body when verification requires it. For an authenticated webhook, verify the signature against the representation covered by the provider’s signing scheme before parsing or transforming the body.
- Decode once according to the documented media type. Reject malformed input instead of passing a partially interpreted value downstream.
- Map source fields and envelopes. Convert source-specific names and nesting into the canonical internal object. Keep this mapping at the ingress boundary rather than scattering it across workflow steps.
- Validate the canonical object against a versioned schema. Check required fields, types, allowed values, and the explicit policy for unknown or privileged fields. A successfully decoded JSON string can still be missing required data or contain the wrong types.
- Pass only the validated object to orchestration. Keep trusted server-generated metadata separate from caller-supplied inputs.
When validation fails, return an actionable error consistent with the endpoint contract. Identify the invalid field or expected shape without exposing secrets or internal implementation details. Parsing and normalization make inputs consistent; validation determines whether they meet the workflow’s requirements.
Webhook-specific integrity and delivery concerns
Webhook signing can depend on the exact transmitted bytes. Standard Webhooks specification v1.0.0 says signatures can cover the webhook identifier, delivery-attempt timestamp, and body together; its example signing input is msg_id.timestamp.payload. Parsing JSON and serializing it again can change whitespace or representation and invalidate a signature. Preserve the raw body and follow the producer’s exact verification rules before normalization.
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Choose a webhook payload shape for the consumer
Standard Webhooks specification v1.0.0 recommends JSON for broad compatibility and recommends including event-specific examples and a formal schema such as JSON Schema or OpenAPI. It describes a conventional event structure with an event type, event timestamp, and event data, while allowing additional metadata at the top level or inside data. It does not mandate one payload schema.
| Payload style | What it carries | Useful when | Trade-offs |
|---|---|---|---|
| Full | Event details and related entity information | Consumers need the relevant information immediately | Can increase transfer and processing cost and expose more data than a consumer needs |
| Thin | Primarily identifiers, sometimes with change information | Consumers should fetch only the details they need, or access should be more controlled | Consumers may need an additional retrieval step; feasibility depends on producer capabilities |
Choose based on what consumers need immediately, transfer and processing costs, producer capabilities, and privacy, access-control, and audit requirements. The specification’s recommendation that typical webhook payloads be smaller than 20 KB is guidance, not a technical maximum or a universal standard.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Test every supported trigger against the same contract
Exercise each ingress path, including direct API calls, against the same canonical schema. Equivalent inputs arriving through supported triggers should produce equivalent canonical objects, even when their transport representations differ.
- Valid input for each supported schema version
- Malformed JSON or other malformed body data
- Missing required fields and wrong field types
- Empty optional values and unknown keys
- Invalid webhook signatures and replayed webhook IDs
- Requests with the wrong envelope or content type
Check both outcomes: valid requests reach orchestration with only the validated canonical object, while invalid requests fail at the boundary with the endpoint’s documented error behavior. For webhooks, also confirm signature verification occurs before any transformation that could change signed bytes.
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