canonical: https://jentic.com/apis/datascreeniq.com/datascreeniq

# DataScreenIQ API

The DataScreenIQ API screens data payloads for quality at the edge, returning a PASS, WARN, or BLOCK verdict in milliseconds. It learns a baseline schema per source and flags rows that drift from it, records each screening as a job for later inspection, and reports aggregate statistics across runs. API keys and billing are managed through the same surface, and a source baseline can be reset when the expected shape changes.

## For AI agents

Screen data payloads for quality and get PASS, WARN, or BLOCK verdicts, inspect past screening jobs, read aggregate stats, and reset per-source baselines. Authenticated with an apiKey in the X-API-Key header across 13 operations.

## Scope

Does not handle data storage, transformation pipelines, or record enrichment with external data. Use for real-time data-quality screening and drift detection only.

## Capabilities

- Screen a data payload and get a PASS, WARN, or BLOCK verdict
- Learn a baseline schema per source and flag rows that drift from it
- List and inspect past screening jobs
- Read aggregate statistics across screening runs
- Reset the baseline for one source or for all sources

## Use cases

### Inline Data-Quality Gating

A pipeline agent screens each incoming payload before it lands in a warehouse. DataScreenIQ returns PASS, WARN, or BLOCK in milliseconds against the learned baseline for that source, so the agent passes clean rows through, routes warnings for review, and blocks malformed batches at the edge.

Example prompt: Call POST `/v1/screen` with the rows and route the batch based on whether the verdict is PASS, WARN, or BLOCK

### Screening Audit and Stats

An operations agent reviews data-quality health over time. It lists past screening jobs, inspects a specific job by id to see why rows were flagged, and reads aggregate statistics to track how often sources drift, feeding a quality dashboard without manual sampling.

Example prompt: Call GET `/v1/jobs` to list recent screenings, then GET `/v1/jobs/{id}` to inspect a flagged job

### AI Agent Integration via Jentic

An AI agent reaches the DataScreenIQ API through Jentic without wiring the X-API-Key header itself. It searches by intent, receives the screen operation and its input schema, and executes with the credential injected at run time, gating its own data writes behind a quality verdict.

Example prompt: Search Jentic for 'screen a data payload', load the POST `/v1/screen` schema, and execute it with Jentic-managed credentials

## Key endpoints

| Method | Path | Description |
| --- | --- | --- |
| POST | `/v1/screen` | Screen a data payload |
| GET | `/v1/jobs` | List screening jobs |
| GET | `/v1/jobs/{id}` | Get a screening job |
| GET | `/v1/stats` | Aggregate statistics |
| DELETE | `/v1/schema/{source}` | Reset the baseline for a source |
| GET | `/v1/keys` | List API keys |
| GET | `/v1/billing` | Get billing info |

## Key resources

- **Screening** — Screen payloads and reset per-source baselines under `/v1/screen` and `/v1/schema`
- **Jobs** — List and inspect past screening jobs under `/v1/jobs`
- **Stats** — Read aggregate screening statistics via `/v1/stats`
- **Keys and Billing** — Manage API keys and billing under `/v1/keys` and `/v1/billing`

## AI readiness

This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.

- **Score:** 64 / 100
- **Maturity:** AI-Aware
- **Dimensions:**
  - Foundational Compliance: 100 / 100
  - Developer Experience & Jentic Compatibility: 62 / 100
  - AI-Readiness & Agent Experience: 44 / 100
  - Agent Usability: 94 / 100
  - Security: 55 / 100
  - AI Discoverability: 71 / 100
- **View full report:** https://jentic.com/apis/datascreeniq.com/datascreeniq/scorecard
- **How the score is calculated:** https://docs.jentic.com/reference/api-readiness-framework/overview/
- **More about the dimensions:** https://docs.jentic.com/reference/api-readiness-framework/specification/#dimensional-model-overview

### Score it yourself

Every API in the directory is allowlisted, so you can re-score it with no key required.

- **Score your own API:** https://jentic.com/scorecard.md
- **Scoring CLI agent skill:** https://github.com/jentic/jentic-api-scorecard/blob/main/skills/jentic-api-scorecard/SKILL.md

```sh
npx @jentic/api-scorecard-cli score <openapi-url>
```

## Why Jentic

- **Setup:** Wiring DataScreenIQ by hand means sending its apiKey in the X-API-Key header to api.datascreeniq.com and threading the PASS, WARN, or BLOCK verdict into your pipeline logic yourself. Through Jentic you install once, import DataScreenIQ from the API Directory, store the key once, and your agent calls it.
- **Permission scoping:** A rule can confine your agent to the screening and read operations it needs, such as submitting payloads and reading stats, because key management, billing, and baseline resets are separate operations you choose to include. Those destructive actions stay out of reach unless you grant them.
- **Credential handling:** Your DataScreenIQ key is stored once, encrypted, by your own Jentic One instance and injected at execution time. It never enters the agent's prompt, logs, or context.
- **Discovery method:** Agents search Jentic by intent such as 'screen a data payload' or 'read screening stats', and Jentic returns the matching DataScreenIQ operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

## Related APIs

- **Soda** — Data quality testing and monitoring for datasets
- **Airbyte** — Data integration and movement between sources and destinations
- **Segment** — Customer data pipeline and event routing

## FAQ

### What authentication does the DataScreenIQ API use?

The DataScreenIQ API authenticates with an apiKey sent in the X-API-Key header per its OpenAPI spec, which also declares a bearer scheme. The health endpoint is public. Through Jentic the key is stored encrypted by your own Jentic One instance and injected at execution time, so it never enters the agent's context.

### What verdicts does the DataScreenIQ screen endpoint return?

The screen endpoint returns PASS, WARN, or BLOCK for a submitted payload, measured against the learned baseline schema for that source. An agent can gate its pipeline on the verdict, passing clean rows and blocking malformed batches at the edge.

### Can I reset a source baseline with the DataScreenIQ API?

Yes. The schema endpoints reset the baseline for one named source or for all sources, which an agent does when the expected shape of a feed changes legitimately. After a reset, subsequent screenings learn and compare against the new baseline.

### How do I screen a payload through Jentic with the DataScreenIQ API?

Search Jentic for 'screen a data payload', and it returns the DataScreenIQ screen operation with its input schema. Load the schema and execute POST `/v1/screen` with the credential injected at run time. To run it on your own infrastructure, install Jentic One from its GitHub repo.

### Can I limit what my agent is allowed to do with the DataScreenIQ API?

Yes. Write a rule that allows only the screening and read operations the agent needs, such as submitting payloads and reading stats, while leaving out API-key management, billing, and baseline resets unless you add them. Each call runs through your own instance and is logged for review.