Canonry ↗
An open-source technical AEO audit library is preferred over a hosted multi-module product.
← All toolsAnother direction / 01 Another direction / 02 Another direction / 03
The selection guideSource-backed research ↗
AI Search Monitoring / Commercial SEO, AEO, and GEO audit platform with rule-based checks and live AI-model scans
CrawlProof
AEO and GEO audits that show what AI crawlers can read, cite, and recommend
AEO/GEO auditingTechnical crawlabilityAI-model auditsRemediation planning
Why it stands out
Connects technical crawlability checks with live AI-model observations.
Source review: · Public-source research, not a hands-on test
↗ Best for
Technical SEO and web teams auditing AI-crawler accessibility.
! Know before you buy
The packet supports active identity, advertised audit scope, public credit pricing, and a public implementation. It does not prove score accuracy, citation precision, repeatability, customer satisfaction, or business impact.
01 / Editorial assessment
Is CrawlProof for you?
The AICiteKit take
CrawlProof is a plausible technical entry point for teams that need to inspect AI-crawler readiness: HTML versus rendered content, schema, robots and sitemap rules, AI-bot access, llms.txt, entity links, agent files, positioning, and live model observations. Rule-based scans are advertised as free up to a daily limit; AI-model scans cost 20 credits, listed as $6 before volume discounts. The checked evidence is vendor-controlled, with no independent product test or representative customer sample found. Use a frozen-URL pilot and manual adjudication; the public sources do not prove score accuracy, citation lift, traffic, or revenue outcomes.
A good fit if you are…
- Technical SEO and web teams auditing AI-crawler accessibility.
- Content and brand teams checking schema, entity links, llms.txt, and positioning.
- Agencies needing a repeatable first-pass GEO/AEO diagnostic.
- Developers who value a public repository and documented audit concepts.
Consider another option if…
- Buyers requiring independent product ratings or controlled benchmark evidence.
- Teams seeking mature prompt monitoring or competitor share-of-voice reporting.
- Buyers expecting audit scores to prove causal ranking, citation, traffic, or revenue improvement.
- Organizations needing a complete public enterprise security and retention matrix.
02 / Scope, not promises
Features & coverage
- Audit scope
Official pages describe checks for HTML/rendered content, schema, robots, sitemap, AI-bot access, llms.txt, knowledge graph, agent files, positioning, and live AI-model answers.
Archived research · Official homepage and about page checked 2026-10-29Research excerpt · Core features and boundaries- Named model coverage
The homepage and pricing page name nine models, including Claude Sonnet 4.6, OpenAI GPT-5 Mini, Gemini 2.5 Pro, Perplexity Sonar Pro, Qwen Max, Kimi v2.6, DeepSeek V4, Z.AI GLM-5.2, and Sakana Fugu.
Archived research · Official homepage and pricing page checked 2026-10-29Research excerpt · Live AI-model audit- Evidence boundary
The packet supports active identity, advertised audit scope, public credit pricing, and a public implementation. It does not prove score accuracy, citation precision, repeatability, customer satisfaction, or business impact.
Archived research · Research dated 2026-10-29Research excerpt · User feedback and evidence quality
Rule-based AEO/GEO audit
Inspect HTML versus rendered content, schema, robots, sitemap, AI-bot access, llms.txt, entity links, agent files, and positioning, then review prioritized findings.
Live AI-model audit
Use credit-based scans to ask named models what they can find, miss, and cite about a site; preserve model, prompt, timestamp, and site-version context for comparison.
Priority remediation workflow
Translate findings into developer-ready tasks, while validating each recommendation against the site and a defined acceptance test rather than treating priorities as proof of impact.
Evidence boundary
Official sources establish scope and commercial terms more strongly than score calibration, citation accuracy, customer satisfaction, or business outcomes.
A focused evaluation workflow
- Submit a URL for a free rule-based audit or a credit-based model scan.
- Inspect crawlability, rendered content, schema, robots, sitemap, AI-bot access, llms.txt, entity links, and positioning.
- Review model answers and prioritized findings, distinguishing observable defects from model judgments.
- Re-run a frozen URL after changes and manually validate whether the configured sample changed.
03 / Commercial boundaries
Pricing & limits
Terms below reflect the 2026-10-29 source review, not a new live quote. Confirm currency, billing term, tax and required scope with the provider.
- Public pricing
Rule-based scans are free up to the daily limit. AI-model scans cost 20 credits and the official page lists $6 before volume discounts; signup includes 20 credits.
Archived research · Official pricing page checked 2026-10-29Research excerpt · Pricing and limits
Additional costs & usage boundaries
Include the usage components listed above in the total cost; they are not separate flat software subscriptions.
Your buying checklist
Get these answers first.
- Which rules, models, regions, prompt settings, and report-retention options apply to my account?
- How is the AEO score calculated, calibrated, and versioned across model changes?
- Can each finding be traced to raw HTML, rendered output, answer text, cited URL, timestamp, and model?
- What are the rate limits, credit expiry, payment, API, webhook, and export boundaries?
- Can raw HTML and model answers be deleted, and what structured findings remain?
- Can a frozen-prompt pilot be compared with manual adjudication before reporting?
Pricing context & qualifications
The official pricing page checked 2026-10-29 lists free rule-based scans up to the daily limit, 20-credit AI scans at $6 before volume discounts, 20 signup credits, and credit bundles. Confirm current limits and payment terms before purchase.
04 / The tradeoffs
Strengths & weaknesses
Reasons to shortlist
- Connects technical crawlability checks with live AI-model observations.
- Public pricing separates free rule-based scans from credit-based model scans.
- Checks specific GEO surfaces including llms.txt, knowledge-graph links, and agent files.
- Prioritized findings can make remediation easier to operationalize.
Reasons to pause
- No independent product test, rating sample, or controlled benchmark was found.
- Public sources do not establish score calibration, citation precision/recall, or repeatability.
- Model, region, prompt, retention, quota, and enterprise security boundaries require verification.
- An audit observation cannot prove causal visibility, traffic, conversion, or revenue lift.
The packet supports active identity, advertised audit scope, public credit pricing, and a public implementation. It does not prove score accuracy, citation precision, repeatability, customer satisfaction, or business impact.
05 / Choose by the job
Alternatives to consider
Editorial fit comparisons—not performance rankings or claims that one option always wins.
SEO/GEO Audit Kit ↗
A focused audit workflow and different implementation boundary fit better.
CiteLadder ↗
Ongoing AI-search visibility and citation tracking matter more than technical readiness checks.
06 / What we can substantiate
Reviews & evidence
Public evidence is stronger for CrawlProof's identity, advertised audit scope, pricing mechanics, and implementation context than for efficacy or customer satisfaction.
AICiteKit assessment: public-source research, not a hands-on product test. Official materials establish stated scope; reviews are dated and may concern the broader platform. Neither establishes guaranteed citations, traffic or revenue.
Sources & original verification dates
| Source | Evidence type | Checked |
|---|---|---|
| CrawlProof official homepage ↗ | Official product page | |
| CrawlProof pricing ↗ | Official pricing page | |
| CrawlProof docs ↗ | Official documentation | |
| CrawlProof about ↗ | Official product and privacy page | |
| CrawlProof GitHub repository ↗ | Public maker-controlled repository; implementation context | |
| Hacker News AI-search visibility results ↗ | Independent community/category context; not a CrawlProof product test |
Original review evidence & date context
Preserved from the published research. Dates, review counts and product-scope qualifications below have not been refreshed by this layout migration.
Medium confidence for active identity, advertised audit scope, public credit pricing, and implementation context; low confidence for score accuracy, citation precision, repeatability, satisfaction, causal lift, traffic, conversion, and revenue outcomes.
Research notes & unresolved discrepancies
- Official homepage, pricing, docs, and about pages are vendor-controlled evidence.
- The public GitHub repository supports implementation/discovery context but is maker-controlled.
- Hacker News search provides category context only; no product-specific CrawlProof review was used.
- No verified G2, Capterra, TrustRadius, Product Hunt, Indie Hackers, or Peerlist product-rating sample was found in this pass.
Layout migration: October 4, 2026. The original MDX research is retained in the repository; this reorganization does not refresh its factual verification dates.