Sample  An abridged sample of a real Coderax scan of basemouse.com. The analysis is unedited; the fix roadmap is trimmed — the full report goes further.Scan my site free
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Coderax
AI Visibility Audit
Sat, 27 Jun 2026 00:48:54 GMT

basemouse.com

https://basemouse.com
44/100
AI Visibility Score — how easily AI answer engines can crawl, classify, explain, and recommend this company.

How to read this report

The score is a legibility measure, not a popularity measure. It rates how easily an answer engine can reach your pages, parse them, and extract facts it can quote. It does not measure how often answer engines currently mention you. A high score means nothing on your site is blocking a citation; earning the citation is the off-site work at the end of this report.

The five categories answer different questions:

CategoryThe question it answers
Positioning clarityCan a model tell what you sell, and to whom, without inferring it?
ICP and conversion clarityIs it obvious who this is for and what the next step costs?
Technical crawlabilityCan a crawler reach your pages and get real content back?
Structured data and answer assetsIs what your pages claim confirmed in machine-readable form?
AI answer readinessDo you have the page types engines prefer to quote — FAQ, comparison, trust language?

Positioning clarity and technical crawlability carry the most weight, because a model that cannot read your pages or cannot tell what you sell has nothing to work with regardless of how the other three score.

Status labels are fixed thresholds: strong is 75 and above, adequate is 50 to 74, weak is below 50. They describe the category score, not your ranking against anyone else.

The evidence checklist is deliberately binary. Each signal is Pass or Needs work with no partial credit, because these are things a crawler either finds or does not. A missing sitemap is not 60% of a sitemap.

Read the categories before the number. Two sites scoring 45 can need completely different work — one blocked at the crawler, one legible but with nothing quotable on the page. The overall score tells you roughly where you stand; the weakest category tells you what to do on Monday.

Executive summary

Top finding: The weakest area is structured data and answer assets at 0/100, the signal AI systems are least able to read on this site.

Biggest gap: Structured data and answer assets is the weakest category; this site is missing sitemap.xml, llms.txt, structured data, entity (sameAs) links, FAQ content, and comparison content that answer engines rely on.

First fix: Start with: publish sitemap.xml and reference from robots.txt (impact high, difficulty low).

Extracted positioning (as AI sees it)

BaseMouse — Top 10 Solar Companies — BaseMouse ranked solar vendors. Rated on brand value, cost-effectiveness, quality, and service. Terminal-grade data, no hype. — GROUND YOUR AGENTS IN YOUR DOCS.

Category scores

CategoryScoreStatusEvidence
Positioning clarity 100/100 strong Specific page title; Useful meta description; H1 names the category/problem
ICP and conversion clarity 55/100 adequate Pricing/plans path detected; Lead capture path detected; Docs/product depth detected
Technical crawlability 20/100 weak Enough crawlable text
Structured data and answer assets 0/100 weak
AI answer readiness 28/100 weak

Evidence checklist

SignalStatusEvidence
robots.txt Needs work No reachable robots.txt was found.
sitemap.xml Needs work No sitemap.xml was detected at the site root.
llms.txt Needs work No /llms.txt was found; AI engines have no curated profile.
JSON-LD structured data Needs work No JSON-LD/schema markup was detected.
Entity links (sameAs) Needs work No sameAs entity links were detected; AI engines cannot connect the site to its official profiles (LinkedIn, GitHub, Crunchbase).
FAQ content Needs work No FAQ content was detected.
Pricing or demo path Pass A pricing/plans path was detected.
Lead capture Pass A lead-capture form or email field was detected.
Comparison/alternatives content Needs work No comparison/alternatives content was detected.
Docs & security depth Pass Docs and/or security/compliance language was detected.

Fix these first

Sequenced by execution dependency — foundational crawlability first, then structured data, then content assets. Only signals weak or missing on this site are listed.

  1. Publish sitemap.xml and reference from robots.txt — A sitemap referenced from robots.txt is foundational crawlability — pages that are not discoverable cannot be read at all.
  2. Add llms.txt — A published /llms.txt gives AI crawlers a curated profile to read instead of inferring positioning from raw HTML.
  3. Add Organization / SoftwareApplication JSON-LD — Structured data lets answer engines classify the product and company from explicit fields rather than guessing from prose.
  4. Declare official profiles with sameAs — sameAs entity links let AI systems verify the company across independent profiles instead of treating it as an unverified entity.
  5. Add FAQ content — FAQ content supplies the direct question-and-answer text that answer engines prefer to quote.

Prioritized recommendations

RecommendationImpactDifficultyWhy it matters
Add llms.txt
Add /llms.txt with a concise AI-readable company profile, key URLs, target ICP, and preferred category language.
High Low A published /llms.txt gives AI crawlers a curated profile to read instead of inferring positioning from raw HTML.
Add FAQ content
Add FAQ content answering category, pricing, security, integration, and “who is this for?” questions.
High Low FAQ content supplies the direct question-and-answer text that answer engines prefer to quote.
Publish sitemap.xml and reference from robots.txt
Publish a sitemap.xml and reference it from robots.txt.
High Low A sitemap referenced from robots.txt is foundational crawlability — pages that are not discoverable cannot be read at all.
Add Organization / SoftwareApplication JSON-LD
Add schema.org JSON-LD for Organization, WebSite, SoftwareApplication/Product, and FAQPage where relevant.
High Medium Structured data lets answer engines classify the product and company from explicit fields rather than guessing from prose.
Create comparison / alternative page
Create comparison/alternatives pages so AI systems can place the product in the right buying context.
High Medium Comparison content gives AI systems the buying context needed to place the product against alternatives.
Declare official profiles with sameAs
Declare your official profiles (LinkedIn, GitHub, Crunchbase) with Organization sameAs JSON-LD so AI engines can verify the company entity across the web.
Medium Medium sameAs entity links let AI systems verify the company across independent profiles instead of treating it as an unverified entity.

Beyond your website: getting cited, not just crawled

On-site fixes make your site legible to AI engines, but engines recommend companies they can find in search indexes and verify across independent sources. Complete the path:

  1. Register with the indexes AI engines read. ChatGPT search reads Bing's index; Gemini and AI Overviews read Google's — an unindexed site cannot be cited.
    • Google Search Console (search.google.com/search-console): add a Domain property, verify with the DNS TXT record, submit your sitemap.xml, then URL Inspection → Request Indexing on your top pages.
    • Bing Webmaster Tools (bing.com/webmasters): use "Import from Google Search Console", or verify the same way.
    • First indexing of a new domain takes days to weeks — start before any content work.
  2. Enable IndexNow — a free protocol that pushes changed URLs to Bing, Seznam, Naver, and Yandex in hours instead of weeks (Google doesn't participate; Search Console covers it). Full report: key generation, the ownership-proof file, and the exact per-deploy ping to wire into your pipeline.
  3. Build the entity triangle. Engines recommend companies they can verify as real, single entities by cross-checking independent profiles — LinkedIn, GitHub, Crunchbase — that all tell the same story and link back to you. Full report: the copy-paste sameAs JSON-LD block, consistency rules, and how to validate it.
  4. Get cited where AI already looks. AI "best tools" answers lean on a small set of roundup articles, community threads, and definitional pages — getting into them beats any volume of social posts. Full report: how to find the exact sources AI cites in your category, which community to start in and why, and the outreach script.
  5. Build branded search volume. Of the standard SEO metrics, this is the one that best separates brands AI recommends from brands it ignores — domain authority and organic traffic predict it at close to chance. Full report: the 2026 research behind this, and where it sits in your sequence.
  6. Baseline and track. Fix a set of buyer questions, ask the assistants monthly, and record whether and how you appear. Full report: the question framework and the before/after method.

This is an abridged sample

The analysis above is real and unedited — that is genuinely how this site scored. The roadmap is trimmed. The full $29 report adds:

Scan my site free →

Generated llms.txt draft

# BaseMouse

> Context infrastructure for AI agents: import your docs, pull cited context packs over one endpoint, and maintain an append-only history of everything your agents were told.

## Primary URL
https://basemouse.com

## About
BaseMouse is context infrastructure designed for AI agents. It allows development teams to import a folder of Markdown documents, retrieve cited and checksummed context packs through a single API endpoint, and preserve an append-only audit history of every piece of context an agent received. The platform is available as a hosted service and as an open-source core that teams can run themselves.

## Products & offering
BaseMouse provides a Context Store (rev 0.3) that handles corpus ingestion, grounded context retrieval, and agent governance. Developers interact through a single API call that returns context packs with full provenance. The platform includes a governance demo, a design-partner intake flow, API access with a published rate card, open-source self-hosting, and documentation.

## Who it's for
BaseMouse is built for engineering teams developing AI agents who need reliable, auditable context grounding rather than ad-hoc prompt stuffing. It is particularly relevant to teams that require provenance tracking, checksummed retrieval, and a verifiable record of what their agents were told during operation.

## Key pages
- Home: https://basemouse.com
- Pricing / Rate Card: https://basemouse.com/pricing
- Documentation: https://basemouse.com/docs
- Open Source: https://basemouse.com/open-source
- API: https://basemouse.com/api
- Governance Demo: https://basemouse.com/demo
- Design Partner Intake: https://basemouse.com/design-partner

## Contact
https://basemouse.com

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