# Publication Records - Unit-Label Consistency Check

> Publication Records - Unit-Label Consistency Check is a paid API for AI agents from www.mahastrategies.com, paid per call via x402, $0.012332/call, status unknown (last checked 2026-10-16).

Validates that declared aggregate count kinds match their unit labels within a single specified source, work, study, or revision record.

## Facts

- Endpoint: POST https://www.mahastrategies.com/api/v1/intel/publication-records/unit-label-consistency?utm_source=zero.xyz
- Price: $0.012332/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/publication-records-unit-label-consistency-check-c00b6d0f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_9H-0IJqLrIVOtyqhVQu_H

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability publication-records-unit-label-consistency-check-c00b6d0f -d '<json body>'
```

Example prompt: Can you check these public measurement records from our study and verify that the declared aggregate count kinds actually match their unit labels? The metadata is non-personal — here are up to 10 measurements to analyze.

## When to prefer this

Choose this endpoint when you need to validate unit-label consistency within a single publication record, study, or revision and your data is pre-scoped to one source. It is suited for pre-submission audits, pipeline quality checks, and revision reviews where the goal is catching count-kind/unit-label mismatches in research or scientific datasets. It is not an independent certification service — use it as a lightweight analytical check on your own supplied records.

## Known failure modes

- Missing or invalid dataClass enum value (must be 'public' or 'synthetic')
- measurements array outside 1–32 item bounds returns validation error
- nonpersonalMetadata not set to true (const:true required)
- Malformed measurement objects in the array
- Ambiguous or unrecognizable unit labels in input data
- Network timeout on large measurement arrays

## How this service works

Check declared aggregate count kinds against unit labels in one exact source/work/study/revision Supplied-record analysis, not independent certification. Full contract at the free describe URL.

## Output

The endpoint returns an analysis of whether the declared aggregate count kinds in the supplied records are consistent with their unit labels, identifying any mismatches or inconsistencies within the single specified source, work, study, or revision. This is a supplied-record analysis, not independent certification.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "dataClass": {
   "enum": [
    "public",
    "synthetic"
   ],
   "type": "string"
  },
  "measurements": {
   "type": "array",
   "maxItems": 32,
   "minItems": 1
  },
  "nonpersonalMetadata": {
   "type": "boolean",
   "const": true
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/publication-records-unit-label-consistency-check-c00b6d0f/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from www.mahastrategies.com](https://www.zero.xyz/host/www.mahastrategies.com/llms.txt)