itpp-infrastructure/projects/seo-visibility-checker/01-product-plan.md

SEO + AI Visibility Checker — Product Plan

Status: OPEN · Draft v1 Date: 2026-08-23 Trigger: Competitor review of tranx.io "Alice" (SEO + AI visibility check)

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1. Why this exists

Two things changed that make a pure Google-only SEO scanner obsolete:

1. AI crawlers are a second index. ChatGPT, Perplexity, Claude, and Gemini answer questions by rendering and retrieving pages — and they each read /llms.txt, robots.txt (AI user-agents), and structured data differently from Googlebot. A site can rank #1 on Google and be invisible to every AI assistant.
2. AI-visibility is not measured by anyone cheap. Screaming Frog / Ahrefs / Semrush measure Google. llms.txt and AI-crawler access are a blind spot. The only tools touching it (Alice, Profound, Peec) are either bare or lock it behind enterprise signup.

We already own the hard parts: Super Search (22 tools, web_extract, AI-answer probing) and a production-tested seo-audit skill with a browser_cdp methodology. This tool is productizing that skill + adding the AI-visibility layer nobody else has.

This follows the existing "obstacles as products" pattern: we needed to SEO-optimize our own 15 sites, so we build the checker first.

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2. Product definition

One-line: A 30-second scan that answers "can Google and ChatGPT/Perplexity/Claude find, render, and cite this site?" — with a 0-100 score, severity-ranked issues, and copy-paste fixes.

Core promise: "Know how visible you are to search and AI — in 30 seconds, no signup."

The five check families (parity with Alice, plus our edge)

Family	Checks
On-page SEO	title, meta description, H1, canonical, Open Graph, structured data (JSON-LD), lang, viewport
Crawlability	robots.txt (status + directive parse), sitemap.xml (status + URL count), HTTPS, redirects (www↔non-www, http→https)
Indexability	brand SERP probe, indexed-page estimate (site: query), sitemap-vs-index gap
AI visibility ← our moat	/llms.txt presence + parse, per-AI-crawler robots directives (GPTBot, ClaudeBot, PerplexityBot, Google-Extended), server-rendered vs JS-only content, schema markup richness, and a live "how does ChatGPT/Perplexity see this brand" probe via Super Search
Measurement	GTM, GA4, Google Ads, Meta Pixel, Klaviyo detection + ID health

Output

• 0-100 score + one-line narrative
• Issues ranked healthy / warning / error with per-issue fix snippets
• Top-3 action list ("moves score most for least work")
• Optional: connect Search Console / GA4 / Ads for query-level depth (Phase 2, paid)

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3. Differentiation vs Alice (tranx.io)

Axis	Alice	Ours
AI visibility	/llms.txt check only	/llms.txt + per-AI-crawler robots + live AI-answer probe (does ChatGPT actually cite this brand?)
Depth	On-page + crawl + index + tags	Same + AI-answer retrieval testing + sitemap/index gap analysis
Stack	Closed SaaS, credit-metered-ish upsell	Super Search backend, self-hosted, MCP-native
Pricing	Freemium, enterprise upsell	Freemium scan + flat monthly (no per-lookup)
Output	Score + issues + top-3	Same + copy-paste fix snippets + export (JSON/PDF)

Moat: the "does an AI actually cite you" probe. That's the question every founder will have in 2026 and nobody answers it in a free tool. It requires an LLM + search backend, which we already run.

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4. Architecture

[Web] seo-check.<tld>  (single-file SPA, static)
   │  POST /scan {url}
   ▼
[FastAPI backend]  :8088  (deploy like other python-web-service-deployment)
   ├─ fetch + parse target (requests + BeautifulSoup + lxml)
   ├─ robots/sitemap/redirect checks (httpx)
   ├─ structured-data validation (JSON-LD parse)
   ├─ llms.txt fetch + parse
   ├─ per-AI-crawler robots analysis
   ├─ JS-render probe (optional headless via existing Crawl4AI / browserless)
   └─ AI-answer probe → Super Search MCP (web_search + web_extract, brand+category query)
   ▼
[Super Search MCP]  (already live, 22 tools)
   └─ "what does {brand} do" → check if brand appears in top AI/search results

Reuse: Super Search (search + extract), Crawl4AI :8910 (JS render when needed), existing seo-audit skill logic as the scoring spec. No new infra — this is a thin FastAPI service on Core behind Caddy.

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5. Build path (phased)

Phase	Scope	Exit criterion
P1 — MVP (free scan)	On-page + crawl + index + AI-visibility (llms.txt + crawler robots + AI-answer probe) + measurement. Score + top-3 + snippets.	Live scan of our own 15 sites, all green
P2 — Auth + depth	Central auth login, saved scans, GSC/GA4/Ads connect, query-level data	Paying first user
P3 — API + MCP	REST API + MCP server (seo-check tool) so Hermes and other agents can run scans programmatically	MCP server live, documented

P1 is the same work as "SEO-optimize our 15 sites" — build the checker, run it on ourselves, fix what it finds. The tool and the site-fix are one effort.

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6. Pricing (value-based, premium — never undercut)

Tier	Price	Includes
Free	$0	1-off scans, rate-limited per IP, no signup
Pro	$29/mo	Unlimited scans, saved reports, scheduled re-scans, AI-answer monitoring alerts
Agency	$99/mo	50 domains, white-label PDF reports, API access
API	usage	Per-scan API + MCP server for agent platforms

Anchored against Alice (free) and Semrush/Ahrefs ($129+/mo). We undercut enterprise but never race to the bottom on the free tier — the free tier is a lead-gen funnel, not the product.

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7. Open decisions (need Germaine)

• Brand/domain: own product name + domain, or a subdomain under an existing property? (Suggests: standalone .io/.com like the other micro-SaaS products — IntelSight, VerdictTank.)
• Scope of "AI-answer probe": how deep — full retrieval comparison or a yes/no "brand cited" flag for v1?
• Ship target: P1 as a free public tool first (lead-gen), or internal-only until our 15 sites are clean?

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8. Immediate next step

The P1 build and the "optimize our 15 sites" ask are the same workstream. Sweep results are in sites-seo-sweep-2026-08-23.md. Fix the 9 failing sites first (proves the scoring model), then ship the checker as a product.