Need Trading-Partner Superset Schema with Per-Partner Validation
Integration platforms exposing data to consumers across thousands of trading-partner relationships need a superset schema for inbound retrieval (so callers see every property and per-partner nuance) paired with per-trading-partner schemas for outbound writes (carrying the required / conditional / optional flags translated from source-system syntax to JSON Schema validation rules).
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Persona Story:
Noah, the head of integration, runs a B2B integration platform with thousands of trading-partner relationships. When his API consumers call GET, they need to see the full union of possible properties across every partner — otherwise they cannot understand the variation in inbound data shapes. When they call POST, they need a schema scoped to the specific trading partner they are writing to — with required, conditional, and optional flags translated from the source syntax (X12, HL7, or a similar legacy contract) into JSON Schema 3.1 validation rules. One direction needs maximum visibility; the other needs maximum specificity. A single normalized schema cannot serve both.
Problem Context
- GET-side consumers want to see every property that any trading partner might send — they will own the mapping into their own ERP, but they can only do that if no information is hidden
- POST-side writers need the schema scoped to the specific trading partner they are writing to, with the source-system conditional-mandatory rules (“if A exists, B must exist”) expressed in JSON Schema 3.1 terms
- A merged superset schema for both directions either over-permits POSTs (validation fails downstream) or over-constrains GETs (consumers can’t see partner-specific variation)
- The conditional-mandatory pattern is the most common point of failure when teams hand-roll their own validation
Problem Impact
- Without superset GET visibility, downstream integrators write defensive code for partner variations they cannot anticipate, multiplying integration cost
- Without per-partner POST validation, payloads pass the 200 OK check but fail at the trading partner; teams discover this hours or days later, after the SLA window has closed
- Hand-rolling validation per trading partner is the dominant cost in B2B integration projects; every team rebuilds the same X12-to-JSON-Schema rules
- Agentic copilots can neither read nor write reliably against the trading-partner network because the schema surface they see does not match the schema the trading partner enforces
Naftiko Today
- A capability YAML can declare both a superset GET schema and per-binding POST schemas; the engine routes requests to the correct schema by trading-partner identifier
- OutputParameters normalization on the GET path preserves the full source variation while presenting a typed consumer contract
- External bindings for credentials per trading partner allow per-partner authentication without code in the capability
- JSON Schema validation runs in-engine, so the 200 OK that consumers see actually reflects whether the payload will validate against the target trading partner’s contract
Naftiko Tomorrow
- OpenAPI-to-Naftiko import (Second Alpha) would let teams generate per-trading-partner capability bindings from an existing superset OAS in one pass
- Schema generation for legacy contracts (Second Alpha) would auto-emit JSON Schema 3.1 rules for required / conditional / optional fields from X12, EDIFACT, and similar source syntaxes
- Reference patterns library (v1.1) would ship the “superset-for-GET, per-partner-for-POST” pattern as a documented capability template
- Fabric capability discovery (v1.1) would surface per-trading-partner bindings in a searchable catalog so teams stop rebuilding the same mappings