Install Jentic One Beta

Connect the NASC - Partner Data API to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the NASC - Partner Data 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%2Fnasc.gov.au%2Fnasc" | 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%2Fnasc.gov.au%2Fnasc" | 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 NASC - Partner Data API.

Submit 1 to 100 scam reports in one dataset_payload, each with scammer contact, impersonation, and loss details

Attach bank_transactions, crypto_transactions, and dce_transactions to a scam report

Poll a submission by response_id for its status and per-record properties_errors

Request scam report data filtered by a date_of_scam_report between two dates

GET STARTED

Start building with NASC - Partner Data API

Explore with Jentic One

View OpenAPI Document

Use Cases

Patterns agents use NASC - Partner Data API for, with concrete tasks.

★ Agent-assisted scam report submission through Jentic

A partner organisation's agent, connected through Jentic, batches the scam reports collected from customers and submits them as one dataset. Each record carries a uid plus fields such as scammer_contact_method, scammer_website_url, how_much_money_was_taken, and consent_to_share_report. The agent then polls the submission by response_id and reports any records that failed validation so staff can fix them.

Call POST /api/v1/datasets/submission with a RequestId header, dataset_version_no, and a dataset_payload of scam_reprot records, then poll GET /api/v1/datasets/submission/{response_id}/response until response_status is completed or failed

Pulling scam report data by date range

To analyse recent scam activity, a partner requests scam report data for a period. The retrieval request takes dataset_version_no and a dataset_filters_payload whose scam_reports_filter sets date_of_scam_report with the between operator and two date-times. The service answers with a response_id, and the agent pages through results as they become available.

Call POST /api/v1/datasets/retreivedata with a RequestId header and a filter on date_of_scam_report between 2026-10-01T00:00:00Z and 2026-10-31T23:59:59Z, then call GET /api/v1/datasets/retreivedata/{response_id}/results/{page} from page 1 while has_more_records is true

Fixing rejected scam report records

When some records in a batch fail validation, the submission status can come back as compeleted_with_errors, the enum value as spelled in the spec. Each failing record lists properties_errors with property_name, record_no, and the error detail, so an agent can correct only those records and resubmit them instead of the whole batch.

Call GET /api/v1/datasets/submission/{response_id}/response, collect every record with properties_errors, and list each property_name and record_no for correction

Key Endpoints

6 endpoints — the nasc partner data api lets partner organisations of australia's national anti-scam centre submit scam reports and retrieve report datasets.

METHOD

PATH

DESCRIPTION

POST

/api/v1/datasets/submission

Submit a scam report dataset

GET

/api/v1/datasets/submission/{response_id}/response

Get submission status and errors

POST

/api/v1/datasets/retreivedata

Request filtered scam report data

GET

/api/v1/datasets/retreivedata/{response_id}/results/{page}

Get a page of retrieved results

GET

/api/v1/metadata

Read API metadata

GET

/api/v1/ping

Check service health

POST

/api/v1/datasets/submission

Submit a scam report dataset

GET

/api/v1/datasets/submission/{response_id}/response

Get submission status and errors

POST

/api/v1/datasets/retreivedata

Request filtered scam report data

GET

/api/v1/datasets/retreivedata/{response_id}/results/{page}

Get a page of retrieved results

GET

/api/v1/metadata

Read API metadata

GET

/api/v1/ping

Check service health

Why Jentic?

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

Setup

Wiring the NASC partner service by hand means sending the API key in a header or query parameter, generating a RequestId UUID for every call, and handling the asynchronous submit-then-poll flow with its misspelled field and path names. Through Jentic you install once, import it from the API Directory, store the key once, and your agent calls it.

Permission scoping

The NASC Partner Data API carries the scam reports and filters inside the request body, so rules bound which operations your agent may call, not which reports. Limit the agent to the operations it needs, such as submitting reports and checking their status.

Credential isolation

Your NASC partner API 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 'submit scam reports' or 'retrieve scam reports by date', and Jentic returns the matching NASC operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

FAQs

Specific to using NASC - Partner Data API through Jentic.

What authentication does the NASC Partner Data API use?

Per its OpenAPI spec, the NASC Partner Data API accepts an API key either in the Api-Key header or in the api-key query parameter. Each operation also requires a RequestId header holding a UUID for the request. Through Jentic, the key is stored once by your own Jentic One instance and injected at call time.

How does submitting scam reports work?

POST /api/v1/datasets/submission takes dataset_version_no and a dataset_payload of 1 to 100 unique scam_reprot records, each with a required uid. It returns 202 with a response_id. Poll GET /api/v1/datasets/submission/{response_id}/response for a response_status of submitted, in_progress, completed, failed, or compeleted_with_errors, along with per-record validation errors.

How do I retrieve scam report data with the NASC Partner Data API?

Send POST /api/v1/datasets/retreivedata with dataset_version_no and a dataset_filters_payload whose scam_reports_filter sets date_of_scam_report with the between operator and two date-times. Then call GET /api/v1/datasets/retreivedata/{response_id}/results/{page}; each page reports page_number, page_size, total_pages, total_records, and has_more_records.

What are the rate limits for the NASC Partner Data API?

The OpenAPI spec does not specify rate limits, and the only server it lists is apidev.nasc.gov.au, a development host. Partner access, production hosts, and limits come from the National Anti-Scam Centre at https://www.nasc.gov.au.

How do I submit scam reports through Jentic?

Install Jentic One with `curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh`, import the NASC Partner Data API from the API Directory, and store your partner API key once. Your agent searches for 'submit scam reports', gets datasets_submission with its input schema, and calls it with your dataset_payload. 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 NASC Partner Data API?

Yes. For a submit-only workflow, write a rule that allows datasets_submission and datasets_submission_status_response, so the agent can send scam reports and check their validation but cannot request or read back report datasets. Add the retrieval operations only for an agent that should analyse report data.

NASC - Partner Data API

AI ReadinessNon-Ready (F)0/100

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Community OpenAPI document · agent-readySecurityThreat DetectionapiKey6 EndpointsREST

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For Agents

Submit batches of scam reports with linked bank, crypto, and exchange transactions to the NASC partner data service, then poll for validation results or pull paged scam report data by report date.

Use for: Submit this week's scam reports to the NASC partner service, Check whether my scam report submission passed validation, Retrieve all scam reports filed between two dates, Get the next page of scam report results

Not supported: Does not block payments, take down scam websites, or accept reports from the public. Use for partner submission and retrieval of NASC scam report datasets only.

The NASC Partner Data API lets partner organisations of Australia's National Anti-Scam Centre submit scam reports and retrieve report datasets. A submission carries 1 to 100 scam_reprot records, each with details such as the scammer's contact method, website, phone, and impersonated entity, the amount taken, consent flags for sharing, and any linked bank, crypto, or digital currency exchange transactions. Both submission and retrieval are asynchronous: the API returns a response_id, and you poll for the processing status, record-level validation errors, or paged results. Retrieval filters scam reports by a date_of_scam_report range.

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

Example Density

How richly the API is illustrated with examples.

100%

Example Validity

Percentage of examples that conform to their schemas.

75%

Response Coverage

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

100%

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: FSignals: 4

19%

Description Coverage

Coverage of descriptions across API elements.

Error Standardization

Coverage of RFC 9457 Problem Details for error responses.

67%

OperationId Quality

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

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: FSignals: 1

33%

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: FSignals: 1

Descriptive Richness

Clarity and depth of descriptions across API elements.

Connect the NASC - Partner Data API to your agent

Capabilities

Start building with NASC - Partner Data API

Use Cases

Key Endpoints

Why Jentic?

Related APIs

FAQs

NASC - Partner Data API

Jentic AI Readiness Score

NASC - Partner Data 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