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Hermes Schema Drift Detector
x402
Hermes Schema Drift Detector is a paid API for AI agents from hermes-counterparty-api.onrender.com, paid per call via x402, $0.015/call, status unknown (last checked 2026-09-15).
Compares two JSON or CSV datasets (current vs baseline) to detect schema drift — added, removed, type-changed, or nullable-changed fields — and flags breaking changes.
Price / call$0.015
Success—
StatusUnknown
How this service works
Agent utilities for company research, package maintenance intelligence, dependency vulnerability checks, counterparty availability, SEC company snapshots, OFAC sanctions screening, and deterministic JSON/CSV data-quality work. Company domain intelligence includes a free preview before the paid enrichment call.
Output
Returns a JSON object listing added_fields, removed_fields, type_changes, and nullable_changes arrays, a boolean breaking_change flag, a schema_version string, and SHA-256 fingerprints for both the current and baseline datasets.
Example use cases
API contract drift monitoring
“My data pipeline ingests a vendor JSON feed daily. Here's yesterday's sample records as the baseline and today's records as current — both JSON format. Tell me if any fields were added, removed, or changed type, and whether it's a breaking change I need to alert on.”
CSV export schema validation
“I have a CSV export from last week as my baseline and a new CSV export from today as current. Can you check whether the schema has drifted — any columns added, dropped, or changed — and give me a fingerprint of each so I can track them?”
Breaking change detection before deployment
“Before I deploy this new API version, compare the baseline JSON records from the old schema to the current JSON records from the new schema and flag any breaking changes like removed or type-changed fields.”
Technical details
Endpoint
POSThttps://hermes-counterparty-api.onrender.com/v1/schema-driftWhen to prefer
Choose this endpoint when you need a deterministic, structured diff of two JSON or CSV schemas — especially when you require a breaking-change flag and field-level fingerprints for audit or alerting. Prefer it over manual diffing or general-purpose LLM comparison when you need a reliable, repeatable schema fingerprint and a machine-readable breakdown of exactly which fields changed and how.
Side effects
- Mismatched format field (e.g. sending 'csv' format key but supplying JSON records) returns a validation error
- Empty records array may produce trivially all-removed or all-added field lists
- Extremely large datasets may time out on the Render-hosted free tier
- Missing required 'format' or 'records'/'data' fields returns a schema validation error
- CSV parsing errors if the data string is malformed
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| current | — | |
| baseline | — |
Output
Schema · Response
{
"type": "json",
"example": {
"added_fields": [
"name"
],
"type_changes": [],
"removed_fields": [],
"schema_version": "1.0",
"breaking_change": false,
"nullable_changes": [],
"current_fingerprint": "sha256:current",
"baseline_fingerprint": "sha256:baseline"
}
}Tags
x402
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