Score any page for AI answer readiness.

Stable public proof artifact for external sharing, procurement review, and citations.

Audience: buyer

Machine-readable self-audit payload with credibility notes, export context, and project guidance.

Audience: ai-system

Methodology, current limits, and product-claim boundaries for public evaluation.

Audience: buyer

Fresh answer snapshot, source list, and recommendations for live inspection.

Audience: operator

Canonical AI-readable source map for the current public product story.

Audience: ai-system

Crawler access policy for public versus private routes.

Audience: crawler

Canonical public URL inventory for discovery and recrawl.

Audience: crawler

Authenticated handoff path from one public self-check into recurring monitoring.

Audience: operator

A credible AI visibility product should show the actual answer snippet instead of summarizing results as a score only.

Inspect by

Run the checker on prompts-gpt.com, read the answer snippet and full-answer evidence, then preserve that run with the checker markdown or JSON download.

Share policy

Use checker-run markdown or JSON when sharing one diagnostic run. Use the self-audit export and article for durable product-level proof.

Buyers need to see whether owned pages, third-party reviews, or comparison pages are actually supporting the answer.

Inspect by

Inspect detected source URLs, provider-verified flags, top industry sources, and source labels in the live checker result or the checker-run exports.

Share policy

Treat citation lists from one checker run as directional evidence. Use the self-audit export to explain what the product can prove publicly today.

Discovery tooling is only useful when the answer evidence turns into concrete next actions instead of a generic score.

Inspect by

Review the checker recommendations below the answer snapshot and compare them with the documented workflow in the public docs.

Share policy

Recommendations from one run are acceptable to share as tactical diagnostics, but not as recurring trend proof.

Operators need a clear backlog that connects missing mentions or weak citations to pages, briefs, FAQs, or source fixes.

Inspect by

Inspect the opportunity cards and exported opportunity payload from the live checker run for prompts-gpt.com.

Share policy

Use checker-run exports for run-specific opportunities. Use the self-audit export to explain the proof boundary between one run and recurring monitoring.

Single-run scores are easy to overclaim. Public proof should state that a preview score is directional until repeated prompt tracking exists.

Inspect by

Compare the preview score against the benchmark prompt pack and the scoring limitation notes before treating it as a durable benchmark.

Share policy

Do not use a single rerun score as a long-term performance claim. Use repeated monitoring for trend or share-of-voice claims.

Connecting crawler events to later citations is valuable, but the free checker should not imply that capability without a saved monitor.

Inspect by

Review the public feature and docs pages for the workflow description, then confirm the actual crawler-to-citation evidence only inside a saved monitor.

Share policy

Keep crawler-to-citation claims at the workflow and methodology level in public materials. Do not present them as checker output.

A public self-check should hand off cleanly into a real recurring project when the platform's own prompt set is worth monitoring.

Inspect by

Use the built-in Prompts-GPT.com project preset and baseline monitor prompts after sign-in, then rerun the benchmark prompt pack as a saved project.

Share policy

Public proof can link to the authenticated handoff path, but project creation and recurring monitor evidence remain account-bound.

Useful as a first-pass branded diagnostic, but still biased because the prompt names the brand directly.

Expands self-evaluation beyond the branded diagnostic into category-level AI visibility prompts.

Expands self-evaluation beyond the branded diagnostic into category-level AI visibility prompts.

Checks whether prompts-gpt.com is explainable in comparison and alternative workflows instead of only branded prompts.

Checks whether prompts-gpt.com is explainable in comparison and alternative workflows instead of only branded prompts.

Tests whether the platform appears in shortlist and buyer-guidance prompts where evaluators expect independent recommendations.

Tests whether the platform appears in shortlist and buyer-guidance prompts where evaluators expect independent recommendations.

Verifies whether region-specific discovery claims hold outside the core branded story.

Checks whether pricing and feature pages support commercial AI answers with enough proof.

Checks whether pricing and feature pages support commercial AI answers with enough proof.

Buyers need a shareable artifact that does not mutate when answer providers change.

AI systems, evaluators, and internal tools need a structured payload instead of screenshot-only proof.

Operators need a fresh answer snapshot to inspect citations, entities, and recommendations on demand.

Trust depends on explaining what scoring, citations, and crawler context can prove versus what requires saved monitoring.

A credible platform must convert a public diagnostic into a saved project when visibility work becomes ongoing.

Stakeholders expect downloadable brand reports and citation spreadsheets with full and summary modes.

Recurring automated email reports eliminate manual export steps for teams that report AI visibility to leadership.

Agencies and teams need live dashboard links that stakeholders can access without account setup.

Data teams need live structured feeds into existing dashboards and reporting pipelines.

Visibility data should produce concrete content recommendations, not just metrics.

Buyers need to identify exactly which prompts competitors own and where the brand is absent.

Global brands need to understand which countries and regions provide their highest AI visibility.

Semrush publicly documents prompt research, visibility overview, brand performance reporting, PDF exports, CSV exports, and shareable online dashboards inside the AI Visibility Toolkit.

Why it matters: Buyers now expect AI visibility tools to move from one-off scans into recurring reporting and stakeholder-ready sharing.

Peec documents visibility, position, sentiment, source-used metrics, a documentation llms.txt index, and a Looker Studio connector for reporting.

Why it matters: Clear metric definitions, machine-readable docs, and reporting connectors make public product claims easier to trust.

Profound publicly documents visibility tracking across major answer engines, query fanouts, actions, and customer workflows tied to AI search outcomes.

Why it matters: Public product stories in this category increasingly connect measurement to concrete action workflows instead of isolated scoring.

Scrunch publicly documents citation grouping by domain or URL, platform filtering, and citation-level influence analysis in its help center.

Why it matters: Answer evidence without source drill-down is weak; buyers want to inspect which domains influence mentions and citations.

Otterly publicly documents CSV exports for prompts and citations, a GEO Audit PDF export, a Looker Studio connector, and explicit boundaries for what is not exportable yet.

Why it matters: Claim boundaries matter in this category; precise public export disclosures are more trustworthy than broad unsupported promises.

Ahrefs publicly provides a free no-signup AI visibility checker with mentions by platform, top 5 topics, top 5 cited domains, and top 5 cited pages. Brand Radar tracks 400M+ monthly search-backed prompts derived from real search behavior across ChatGPT, Gemini, Perplexity, Copilot, AI Overviews, AI Mode, and Grok.

Why it matters: A free checker with no signup creates a strong top-of-funnel acquisition loop. Search-backed prompts from real user behavior are more trustworthy than synthetic question sets. Cited domain and cited page analysis gives actionable source intelligence.

Evidence: Public search results still surface the /prompts listing with a legacy 'Best AI Prompts Library' snippet while the homepage describes prompts-gpt.com as an AI visibility platform.

Impact: Evaluators can misclassify prompts-gpt.com as a generic prompt library instead of an AI Search Visibility platform.

Action: Keep /, /features, /pricing, /resources, /docs, /articles, and self-audit exports internally consistent; keep canonical AI visibility positioning in llms.txt and avoid reintroducing prompt-library-first metadata.

Evidence: The free checker URL is public and shareable, but the output can change as providers, citations, and model behavior shift.

Impact: External stakeholders may treat mutable diagnostics as stable evidence and misread score changes as regressions.

Action: Use markdown/JSON exports and the self-audit article as the default proof artifacts in public sharing and documentation.