Install Jentic One Beta

Connect the DataScreenIQ API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the DataScreenIQ API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.

Step 1: Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fdatascreeniq.com%2Fdatascreeniq" | sh

Step 2: Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fdatascreeniq.com%2Fdatascreeniq" | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with DataScreenIQ API.

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

GET STARTED

Start building with DataScreenIQ API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use DataScreenIQ API for, with concrete tasks.

★ 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.

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.

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.

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

Key Endpoints

13 endpoints — the datascreeniq api screens data payloads for quality at the edge, returning a pass, warn, or block verdict in milliseconds.

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

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

Why Jentic?

What agents get from Jentic-routed access to this vendor.

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 isolation

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.

Intent-based discovery

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.

FAQs

Specific to using DataScreenIQ API through Jentic.

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.

DataScreenIQ API

AI ReadinessAI-Aware (B)64/100

See full scorecard

Official vendor OpenAPI document · agent-readyData EnrichmentData TransformationapiKey13 EndpointsREST

For 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.

Use for: Screen a batch of rows and get a quality verdict, Check whether an incoming payload passes data-quality rules, List the recent screening jobs, Get the aggregate screening statistics

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

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.

Jentic One on Github View OpenAPI Document

Show dimension breakdown

100

Foundational Compliance

Base layer of spec validity and structural soundness.

Grade: A+Signals: 4

98%

Lint Results

Aggregated quality score from linter diagnostics, weighted by severity.

100%

Resolution Completeness

Percentage of `$ref` references that resolve successfully.

100%

Specification Validity

Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).

100%

Structural Integrity

Structural correctness score based on schema issues using logarithmic dampening.

Developer Experience & Jentic Compatibility

Clarity, completeness, and ingestion readiness for developers and tooling.

Grade: B-Signals: 4

23%

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

31%

Response Coverage

Percentage of operations with complete response definitions (success, client error, server error).

93%

Tooling Readiness

Health of API ingestion, bundling, and resolution within Jentic pipelines.

AI-Readiness & Agent Experience

Semantic breadth, depth, and agent comprehension for AI systems.

Grade: DSignals: 4

25%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

100%

OperationId Quality

Coverage, uniqueness, and casing consistency of operationIds for AI inference.

52%

Summary Coverage

Coverage of summaries across operations/tags/info.

Agent Usability

Functional utility, complexity comfort, and AI orchestration readiness.

Grade: A+Signals: 1

94%

Complexity Comfort

Agent comfort level based on API operational and structural complexity.

Security

Trust, risk posture, and security compliance.

Grade: CSignals: 1

55%

Authentication Strength

Average quality of security schemes based on authentication method strength (weakest link for OAuth2).

AI Discoverability

Findability, semantic richness, and reasoning readiness.

Grade: A-Signals: 1

71%

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the DataScreenIQ API to your agent

Capabilities

Start building with DataScreenIQ API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

DataScreenIQ API

Jentic AI Readiness Score

DataScreenIQ API

Foundational Compliance

Lint Results

Resolution Completeness

Specification Validity

Structural Integrity

Developer Experience & Jentic Compatibility

Example Density

Example Validity

Response Coverage

Tooling Readiness

AI-Readiness & Agent Experience

Description Coverage

Error Standardization

OperationId Quality

Summary Coverage

Agent Usability

Complexity Comfort

Security

Authentication Strength

AI Discoverability

Descriptive Richness