canonical: https://jentic.com/apis/auditae.app/auditae

# Auditae App AuditAE REST API

The AuditAE REST API checks whether AI answer engines such as ChatGPT, Perplexity, Gemini, and Google AI Overviews cite a brand, and audits the technical signals that make a site answer-ready. It runs a single prompt across engines, runs a broader audit and returns its result by id, crawls a site, and checks one page's technical setup. It also generates and validates schema.org JSON-LD and discovers a brand's entity on Wikidata. Paid calls draw from a prepaid workspace balance, which the billing operations report and top up.

## For AI agents

Check whether AI answer engines cite a brand, crawl and audit pages, and generate or validate schema.org JSON-LD, across 10 endpoints secured with a bearer API key.

## Scope

Does not run paid search ads, manage backlinks, or track keyword rankings. Use for auditing AI answer-engine citations and schema.org structured data only.

## Capabilities

- Check whether AI answer engines like ChatGPT, Perplexity, and Gemini cite a brand for a given prompt
- Run a broader answer-engine audit and fetch its result by id
- Crawl a site and check a single page's technical setup
- Generate schema.org JSON-LD and validate existing JSON-LD markup
- Discover a brand's entity on Wikidata and read the workspace balance and prices

## Use cases

### Answer-Engine Citation Monitoring

See whether AI answer engines mention a brand before competitors notice. An agent sends a prompt to the check operation, reads which of ChatGPT, Perplexity, Gemini, and Google AI Overviews cite the brand, and runs a wider audit to track coverage over time. The result is a concrete citation map an agent can report against.

Example prompt: Run a check for a prompt, then start an audit and poll its result by id

### Schema and Technical Readiness

Make a site easier for AI answer engines to read. An agent crawls the site, checks one page's technical setup, then generates schema.org JSON-LD and validates existing markup. This closes the structured-data gaps that keep a page from being cited.

Example prompt: Crawl a site, generate JSON-LD for a page, then validate the resulting markup

### AI Agent Integration via Jentic

An AI agent discovers and calls AuditAE through Jentic without handling the ae_live key directly. The agent searches by intent, receives the matching operation and its input schema, and runs the check or audit while Jentic injects the stored key. Paid calls draw from the prepaid balance the agent can read first.

Example prompt: Search Jentic for 'check answer-engine citations', load the operation schema, and run the check with Jentic-injected credentials

## Key endpoints

| Method | Path | Description |
| --- | --- | --- |
| POST | `/api/v1/check` | Check one prompt across answer engines |
| POST | `/api/v1/audits` | Run an audit |
| GET | `/api/v1/audits/{id}` | Get an audit result by id |
| POST | `/api/v1/crawl` | Crawl a site |
| POST | `/api/v1/schema/generate` | Generate schema.org JSON-LD |
| POST | `/api/v1/entities/discover` | Find a brand on Wikidata |

## Key resources

- **Citations** — Check a prompt across answer engines and run broader audits
- **Technical** — Crawl a site and check a single page's technical setup
- **Schema** — Generate and validate schema.org JSON-LD, and discover entities on Wikidata
- **Billing** — Read the prepaid balance and prices, and top it up

## 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:** 67 / 100
- **Maturity:** AI-Aware
- **Dimensions:**
  - Foundational Compliance: 93 / 100
  - Developer Experience & Jentic Compatibility: 70 / 100
  - AI-Readiness & Agent Experience: 46 / 100
  - Agent Usability: 94 / 100
  - Security: 60 / 100
  - AI Discoverability: 81 / 100
- **View full report:** https://jentic.com/apis/auditae.app/auditae/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 AuditAE by hand means creating an ae_live_ key, sending it as a Bearer token on auditae.app, and tracking your prepaid balance so paid calls do not fail with a top-up request. Through Jentic you install once, import AuditAE from the API Directory, store the key once, and your agent calls it.
- **Permission scoping:** Through Jentic you limit the agent to the operations it needs, such as running citation checks and audits, while leaving the billing top-up operation out of the set so it cannot spend your prepaid balance.
- **Credential handling:** Your AuditAE 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 'check answer-engine citations' or 'generate schema JSON-LD', and Jentic returns the matching AuditAE operation with its input schema so the agent calls the right endpoint without browsing the reference docs.

## Related APIs

- **Ahrefs** — Classic search-engine SEO metrics, versus AuditAE's focus on AI answer-engine citations.
- **SEMrush** — Broad SEO and competitive analytics, versus AuditAE's answer-engine and schema auditing.
- **Moz Links** — Link authority metrics to pair with AuditAE's answer-engine readiness checks.

## FAQ

### What authentication does the AuditAE REST API use?

The AuditAE REST API authenticates with an ae_live_ key sent as a Bearer token in the Authorization header, per its OpenAPI spec. The same key draws paid calls from your prepaid workspace balance. Through Jentic the key is stored encrypted by your own Jentic One instance and injected at call time, so it never reaches the agent.

### Is there an AuditAE MCP server?

You do not need a separate MCP server to give your agent AuditAE. Jentic connects it directly from the API Directory: import AuditAE, store your key once, and your agent calls its check, audit, and schema operations on demand. Operations are discovered as needed, so no extra server's tool definitions load into the agent's context.

### Can I check whether ChatGPT cites my brand with the AuditAE REST API?

Yes. Send the prompt to the check operation and the API returns which answer engines, including ChatGPT, Perplexity, and Gemini, cite the brand. Run the audit operation for a broader sweep and fetch its result by id.

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

Yes. Because you run Jentic One yourself, your rules decide which AuditAE operations the agent may call. You can allow the citation checks and audits while withholding the billing top-up operation so the agent cannot spend your prepaid balance, and every call is logged.

### What are the rate limits for the AuditAE REST API?

The OpenAPI spec does not specify request rate limits; instead, paid calls draw from a prepaid balance and free calls do not. Read the balance and prices on the billing operation, or see the AuditAE documentation at https://auditae.app for current terms.

### How do I check answer-engine citations with the AuditAE REST API through Jentic?

Search Jentic for 'check answer-engine citations' to get the matching AuditAE operation and its input schema, then your agent runs the check and parses which engines cite the brand. To run it on your own infrastructure, install Jentic One from its GitHub repo.