# Nostalgai — Free deterministic scanner that scores a public website's answer-readiness across 16 observable checks.

> Source: CitedIndex — https://citedindex.com/nostalgai-free-answer-readiness-scanner (structured, researched, re-verified)
> Facts last verified: 2026-08-27

Nostalgai is a free, deterministic scanner that evaluates a public website's answer-engine readiness across sixteen observable checks grouped into identity, access, proof, and decision support. The scanner runs in roughly ten seconds against one homepage plus /robots.txt and /llms.txt, returns a 100-point score with cited evidence behind each result, and stores nothing. It is a diagnostic, not a monitoring tool: there is no API, no AI model calls, no traffic measurement, and no promise of citation outcomes.

| Fact | Value |
| --- | --- |
| Website | https://nostalgai.us/scanner |
| Pricing | Free scanner (16 deterministic checks, no signup, no API key, results not intentionally stored). Paid Fix Pack is $149 founding price: one public English-language site up to 10 pages, three-business-day turnaround; deliverables are an audience-question and page-gap map, three publish-ready answer blocks, one supported JSON-LD bundle, and a prioritized implementation plan. Implementation help and multi-site work quoted separately. |
| API | No |
| Best for | Solo founders and small operators who want a free, transparent, one-shot AEO readiness score before committing to a paid audit or ongoing subscription. |
| Not for | Anyone looking for ongoing AI visibility monitoring, share-of-voice tracking across answer engines, or a guarantee that a specific model will cite them — the vendor is explicit that the scanner does not query models, predict citations, or measure traffic. |

## Pricing

| Tier | Price |
| --- | --- |
| Scanner | Free (ongoing) |
| Fix Pack (founding offer) | $149 / one-time |

## Verdict

Nostalgai earns its slot by being one of the few AEO scanners on this site that is genuinely free, genuinely inspectable, and honest about its limits. Every score line carries the excerpt or element that drove the verdict; the method is published; the scanner stores nothing. The trade-off is that it is a one-person operation: the scanner itself is a deterministic check on one page at a time, and the paid Fix Pack is delivered manually. Buyers expecting ongoing AI visibility monitoring, share-of-voice tracking, or a promise that any specific model will cite them should look elsewhere — the vendor says so up front. For a solo operator or small team that wants a defensible, reproducible baseline answer to 'is my homepage ready to be picked up by AI answer engines' before committing to a deeper audit, this is the cheapest and most transparent starting point we list.

## How it works

1. Paste a public homepage URL into the scanner form.
2. The tool fetches the page, /robots.txt, and /llms.txt on demand.
3. Sixteen deterministic pattern checks run against the markup and content.
4. Each check returns a verdict, the observed excerpt, and the element or URL it inspected.
5. A 100-point score appears in roughly ten seconds with the full evidence behind every line.
6. A separate, paid Fix Pack turns the gaps into a publish-ready implementation package.

## Who it's for

- Solo founders and small operators running their own marketing
- Independent practices and local businesses with a public service to explain
- Marketing and web teams preparing for AI-driven discovery
- Agencies looking for a defensible third-party baseline before pitching AEO work

## Strengths and weaknesses

- ✓ Every score line carries the observed excerpt or element that produced the verdict — the verdict is reproducible from the underlying page.
- ✓ Free, no signup, no API keys, nothing stored.
- ✓ The methodology and point weights are published in full, with a sample self-audit that shows what the scanner cannot catch.
- ✓ The vendor is explicit about what the scanner does not do — no model calls, no citation prediction, no traffic measurement.
- ✗ Operated by one person (Sarah van Oorsouw) — the paid Fix Pack is a manual delivery, not a productized service.
- ✗ The scanner runs against one page at a time, so a full-site audit requires multiple runs.
- ✗ Does not query AI models, predict citations, or measure traffic — buyers expecting 'will ChatGPT cite me?' will not find an answer here.
- ✗ No public API; only the web form is available.
- ⚠ Deterministic pattern checks can miss equivalent language or award points to weak content.
- ⚠ /llms.txt is treated as a low-weight convenience signal, not a ranking factor.
- ⚠ Passing a check means a signal exists; it does not mean the content is accurate or persuasive.
- ⚠ High-stakes medical, legal, or financial claims require qualified review beyond this clarity audit.

## Key features

- **Sixteen observable checks** — Covers identity, crawler access, attributable proof, and decision-support signals. Every check returns the observed excerpt or element that drove the verdict, so the score is reproducible.
- **Inspectable evidence behind every line** — Each score item points to the exact URL, element, or excerpt that was tested. The scanner does not return a verdict the reader cannot re-derive from the underlying page.
- **No signup, no API keys, nothing stored** — Inputs are not retained. The page is fetched on demand, scored, and the result is rendered immediately.
- **Free to run, paid to ship** — The scanner is free. A separate, fixed-price Fix Pack is offered to convert the findings into a publish-ready implementation package.
- **Explicit no-guarantees framing** — The vendor publishes the limits of the method up front — deterministic checks can miss equivalent language or award points to weak content.
- **Public methodology with point weights** — Each check carries a published point value and weight, and the full rubric is available at /method.

## Use cases

- **Quick AEO readiness check** — A founder wants a defensible yes/no answer on whether their homepage currently gives AI answer engines enough to work with — without paying for a full audit or signing up for a monitoring subscription.
- **Pre-redesign baseline** — A team planning a homepage redesign wants a reproducible baseline score they can re-run after the relaunch and compare the before/after against.
- **Sales conversation opener** — An agency or consultant uses the scanner to generate a third-party score they can walk a prospect through before pitching deeper AEO work.
- **AEO education** — A team new to answer-engine optimization wants to see what 'good' looks like on a real site, with the same instrument they can later run on their own homepage.

## Sources

- https://nostalgai.us/scanner
- https://nostalgai.us/scanner-methodology
- https://nostalgai.us/fix-pack
- https://citedindex.com/nostalgai-free-answer-readiness-scanner