BÚSQUEDA CON IA · GEO

Tu sitio
como lo lee la IA.

Qué rastreadores de IA pueden llevarse cada página, cómo se divide una página en los fragmentos que un asistente puede citar, de qué trata el sitio por significado y qué páginas compiten por la misma respuesta. Medido en tu ordenador, con embeddings locales.

Al descargar aceptas los términos de la preview de GLLmolfar.

Documentación
Preparación para IACaptura · 0.9.29

Un rastreo,
todas las formas de leerlo.

El mismo rastreo de getlooploop.com, abierto en las vistas que importan para la búsqueda con IA, para el significado y para el SEO clásico. Nada aquí es una maqueta.

De los datos del rastreo
a la siguiente decisión.

Al descargar aceptas los términos de la preview de GLLmolfar.

Empieza por lo general, acota a un grupo de URL y revisa la evidencia. La app reúne los datos y el camino a la acción en un mismo espacio de trabajo.

Preparación para IA

Si los rastreadores de IA pueden descargar el sitio, las reglas de robots.txt por bot, llms.txt y lo bien que cada página se divide en fragmentos que un asistente puede citar. Cambia entre los modos Hybrid y AI para ver el mismo rastreo desde ambos lados. La app lee el sitio; no mide si los asistentes te mencionan.

Una página, fragmento a fragmento

Los principales grupos de significado de una página, dónde está cada fragmento de arriba abajo, los términos recurrentes y cuánto se ajusta cada fragmento al título y al H1. Sirve para detectar secciones que se desvían del tema declarado.

Temas, solapamientos y oportunidades de enlace

Agrupa páginas por significado y explóralas en el mapa de temas. Compara páginas del mismo idioma inusualmente parecidas con sus fragmentos y señales en común. Las oportunidades de enlace emparejan una página con menos de cinco enlaces entrantes con páginas relacionadas que no la enlazan. Son pistas para revisar, no una prueba de canibalización en buscadores.

Mapa de canibalización

Las páginas que compiten, dibujadas y no solo listadas: cada grupo como un círculo de sus páginas unidas por pares, con los pares más cercanos marcados; cuánto se parecen los pares, qué tamaño tienen los grupos, en qué temas están y un grupo como matriz de similitud.

Mapa de página y mapas de calor

En la auditoría de URL, la página renderizada se convierte en una imagen dividida en bloques y coloreada de cuatro formas: significado frente a una pregunta, lo que citaría un recuperador de IA, hallazgos de accesibilidad y una previsión de atención solo por el diseño (no el comportamiento de personas, y la pantalla lo dice). Sitio › Mapa de calor muestra las carpetas del rastreo como mosaicos coloreados por problemas o clics de Google.

Herramientas gratuitas de GetLoopLoop

Vectorscope, Voicescope, Brandscope, Reviewscope y PatternScope están en Herramientas, en la barra lateral, cada una como la herramienta sola: el campo, el botón y la lectura, sin salir de GLLmolfar. Abrir en el navegador lleva a la página completa en getlooploop.com. Los usos en la app se cuentan en el servidor de GetLoopLoop, aparte de los del sitio web.

El significado se calcula
en tu equipo.

Tras la primera descarga, el modelo de embeddings se ejecuta en local. GLLmolfar usa los vectores para agrupar páginas relacionadas, buscar por significado, comparar fragmentos y dibujar el mapa de temas.

Las páginas largas se dividen por los encabezados H2 cuando es posible. Los vectores de sus fragmentos se combinan en una representación de la página, así una sección profunda también cuenta en la comparación. Cuatro modos leen más o menos de cada página con el mismo modelo: el Ampliado lee el doble que el Estándar y en nuestra prueba encontró la página correcta más a menudo, a cerca de la mitad de velocidad. Los ajustes prueban cada modo en tu equipo con tus páginas. Los modos además del Estándar requieren una cuenta gratuita.

Modelo localSin texto generadoCola opcional
Cómo leer la similitud
Vectores de página cercanosContenido relacionado que revisar
Fragmentos compartidosIndicio de significado repetido
Pocos enlaces internosPosible oportunidad de enlace
Una señal para revisión humana. No es una posición en buscadores ni una medida de tráfico.

Una herramienta de escritorio.
Un límite claro para los datos.

La base de datos de rastreos y el historial se quedan en la carpeta local de la app. Los vectores semánticos se calculan en el equipo tras descargar el modelo. El rastreo sigue enviando peticiones al sitio, y la revisión opcional de enlaces externos contacta con los sitios enlazados.

GLLmolfar no envía tu rastreo a ningún servicio de IA en la nube. El primer análisis semántico descarga el modelo a tu equipo.

Lo que sí envía a getlooploop.com es poco y está descrito: estadísticas de uso anónimas —un ID de instalación aleatorio, la versión de la app, la versión de Windows o macOS, el idioma y cuánto tiempo está abierta; nuestro hosting añade el país que ve para la conexión, nunca la dirección— y una comprobación de nueva versión. Ambas se desactivan en Ajustes.

GLLmolfarPreview de escritorio para Windows y Mac
Preview 0.9.29
Registros de rastreoSQLite local
EmbeddingsEn el equipo, opcionales
Peticiones de rastreoSitio que rastreas
Estadísticas de usoAnónimas, desactivables
Datos de Search ConsoleGoogle → tu equipo
Tú eliges la URL y el alcance del rastreo
HABILIDADES DEL AGENTE · LISTAS DE CONTROL DESDE 0.9.26

20 trabajos listos
para tu propio agente de IA.

Conecta Claude Code, Codex, Cursor u otro agente a GLLmolfar una vez. Cada habilidad le dice qué herramientas de GLLmolfar llamar, en qué orden, qué devolver y cuándo el trabajo está hecho. Antes de cambiar código o rastrear un sitio ajeno, te pregunta. El agente trabaja en la ventana de la app, donde ves cada paso. Los ejemplos de abajo son respuestas reales, no maquetas.

  1. Conecta tu agente en Ajustes › Agentes de IA (MCP).
  2. Si tu agente muestra prompts MCP, ejecuta una habilidad como comando de barra por su nombre.*
  3. O copia el texto de la habilidad y pégalo en tu agente.

Búsqueda con IA

B2Auditoría de preparación para IA del sitio (GEO, AEO)

«¿Pueden ChatGPT, Claude y Perplexity leer y citar mi sitio?»

/ai-readiness*
7 herramientas

Herramientas de GLLmolfar que llama: get_statusget_ai_readinessget_fixesget_fix_urlscount_pagesaudit_urlexplain_fix

Rellenas: site, max_urls, template_urls

Ver una respuesta real

Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026, texto de la habilidad de 0.8.1 · 60 s · 14 llamadas a herramientas de GLLmolfar · sin editar, en inglés

GetLoopLoop.com AI search audit

Sources: "Crawl" means GLLmolfar crawl #32, the open crawl (start URL https://www.getlooploop.com/, 300 of 300 URLs, 300 embeddings). The tool results gave no crawl date. "Probe" is the AI bot check run 2026-10-28 13:36 UTC. "Audit" is a URL audit of 2026-10-28 14:03 UTC. Search Console was not used.

Top 3 changes

  1. Add named authors and visible dates to the content templates. (P1)
  2. Crawl: 225 URLs (75%) have long pages without an author. 218 URLs (72.7%) have no date.
  3. The glossary page I audited shows "Written by Prepared at GetLoopLoop" and "Updated September 2026". That is no named person.
  4. The audited home page and /news have no author and no dateModified. Their datePublished is identical (2026-10-16T10:32:57Z), which looks like a template default. That is my judgment.
  5. Add a byline to an author page and a Person with sameAs in the Article schema. Add datePublished and dateModified per page. This unblocks trust signals, which are the weakest part of the score (36).
  6. To verify, run audit_url on one page and check trust.author and the dates. Then run a new crawl and check ai.noAuthor and ai.noDate.
  7. Source the claims on the glossary and skills pages. (P1)
  8. Crawl: ai.claims affects 42 URLs. 33 of them are under /skills/. The rest are /glossary/, /ai-volatility, /gllmolfar, /questions and /voicescope.
  9. Audit of /glossary/ai-visibility: it has 0 stat sentences. It does make unsourced assertions: "Earn at least three high-quality backlinks", and a first-person "Worked example" about "BrandX" with no source. My judgment is that these read as invented illustration.
  10. Link each figure or example to its source next to the sentence. Mark illustrations as hypothetical.
  11. To verify, run a new crawl and check ai.claims.
  12. Fix the required schema properties. (P2)
  13. Crawl: structured.errors affects 156 URLs (52%). The home page is one. Audit: it lists SoftwareApplication.aggregateRating|review as missing.
  14. Add the missing property, or remove the markup that cannot be filled honestly. Google requires it for the rich result. This unblocks eligibility for that rich result.
  15. To verify, run audit_url on the home page and check that schemaErrors is empty.

No P0 findings. In this crawl, probe and audit I found no content that needs JavaScript, no blocked search bot and no bot wall.

P0

None found.

  • JavaScript (audit): raw and rendered word counts are the same on all three pages: home 1,931/1,931, /glossary/ai-visibility 1,006/1,006, /news 1,108/1,108. 0 words appear only after JavaScript. The only JS difference is 2 links on each page.
  • Search bots (probe): no AI bot is blocked in robots.txt, and every path listed is allowed. All 10 pages fetched as OAI-SearchBot and Claude-SearchBot came back OK, with 0 challenge, 0 blocked and 0 robots.

P1

  • Author and dates are in the Top 3 above.
  • Claims without sources are also in the Top 3 above.
  • Low main-content share: crawl ai.lowMain affects 21 URLs (7%). All are under /skills/* (templates such as affaan-m/ecc: 4 URLs, and open.feishu.cn, open.larksuite.com and code.deepline.com: 2 each). In the audit, chrome words are small on the three pages: 93 of 2,247 on home, 164 of 1,306 on the glossary page, 87 of 1,684 on /news. They are not low-main pages.
  • Passages that need an earlier passage: crawl ai.dangling affects 7 URLs. 3 are /glossary/, and there is 1 each for /legal/, /news/, /vectorscope and /vectorscope/. Open each section with its subject.
  • Walls of text: crawl ai.walls affects 67 URLs, 14 of them under claude-seo. It is low importance. Add a heading every few paragraphs.

P2 (key fixes by template, crawl)

FixURLsMain templates
ai.noAuthor225/glossary/* 100, claude-seo 25, wshobson 8
ai.noDate218/glossary/* 100, claude-seo 25, wshobson 8
ai.walls67claude-seo 14, marketingskills 7, wshobson 7
ai.claims42claude-seo 14, marketingskills 6
ai.lowMain21affaan-m/ecc 4
ai.dangling7/glossary/* 3
structured.errors156claude-seo 25, affaan-m/ecc 11, google/skills 10
nonIndexable6/skills 6 (all)
  • nonIndexable: all 6 pages are on the /skills template. Check whether they should be indexed. If they should, remove the noindex or point the canonical at the page itself.
  • Other crawl findings:
  • cannibal (14 URLs, high).
  • hreflang.noReturn (6, high) and hreflang.missingSelf (6).
  • a11y.unlabeled (1, high).
  • images.missingAlt (41). The audit shows 22 of 30 images without alt on home, and 6 of 6 on the glossary page.
  • 58 external 4xx links.
  • 14 http:// links.
  • 23 pages under 250 words.
  • Duplicate titles (7), duplicate descriptions (7) and duplicate H1s (7).
  • Over-long titles (137), descriptions (131) and H1s (148).
  • 10 slow URLs.
  • Missing X-Content-Type-Options (300 URLs).
  • Cookies without Secure (299 URLs).
  • Not in the fix list: jsContent, javascript.* and noInlinks do not appear, so I did not count them.
  • Audit: all three audited pages show inSitemap: false and 0 inlinks. These are single-page audit rows, so I am not confident they reflect the crawl. Confirm in the crawl before acting.

Google: SEO basics

  • Googlebot (audit): allowed on all three pages (robots.txt lines 2, 17 and 13). All three are indexable with 200 status and a self-canonical.
  • Titles and descriptions (audit): home title is 57 characters (528 px). /news title is 60 characters (594 px), over the 580 px cut. Descriptions are within limits. In the crawl, 122 titles are over 580 px.
  • Duplicate and hreflang issues (crawl): 14 pages near-duplicate another page. 7 titles and 7 descriptions are duplicated. 6 URLs have hreflang return-link or self-reference problems. Fix these to avoid split signals.
  • Schema (audit): the home page has Organization, WebSite, SoftwareApplication, WebPage, FAQPage and ItemList. It has one error and two warnings (Offer.url, ListItem.item). The glossary page has no schema errors.
  • Performance and headers (audit): response times were 1.3–1.7 s on the three pages, and the crawl lists 10 URLs over 1 s. cache-control is no-store on all three. That is my judgment: a cacheable response might help speed.
  • Accessibility (audit): axe flagged colour contrast, definition-list structure and a label mismatch on home. /news has no <main> landmark.

Other engines: structure a retriever can extract

  • AI readiness (crawl #32, probe): score 87/100. The four parts are access 100 (weight 0.35), readability 91 (0.30), meaning 95 (0.20) and trust 36 (0.15). This is GLLmolfar's score, not a ranking factor.
  • robots.txt per bot (probe): all allowed on /, /skills/, /glossary/, /news/, /notes/, /legal/, /vectorscope/, /free-tools/ and /ai-volatility/. Blocked paths: none for any bot.
  • Search: OAI-SearchBot (OpenAI), Claude-SearchBot (Anthropic), PerplexityBot and Amazonbot. All allowed.
  • User: ChatGPT-User, Claude-User and Perplexity-User. All allowed.
  • Training: GPTBot, ClaudeBot, Google-Extended, Applebot-Extended, CCBot, Bytespider and meta-externalagent. All allowed. Allowing training bots is a choice. It does not affect the search bots.
  • Fetch as each bot vs a browser (probe): for the 10 bots that were fetched (GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, Claude-SearchBot, Claude-User, PerplexityBot, Perplexity-User and Amazonbot), each result was 10 OK, 0 less content than the browser, 0 challenge, 0 blocked and 0 robots. That matches the browser. Google-Extended, Applebot-Extended, CCBot, Bytespider and meta-externalagent were checked in robots.txt only, with no fetch.
  • llms.txt (probe): found at 33 KB, titled "GetLoopLoop", with 32 links, 15 sections and 0 broken links. llms-full.txt was not found.
  • Markdown for agents (probe): not offered on the 3 URLs tested. The Accept: text/markdown header returned text/html, and the .md twin returned 404. HTML is fully readable without JavaScript, so this is optional. It would let agents fetch a cleaner copy. To verify, run the probe again.
  • Structure (audit):
  • Home has 5 question-style headings, 19 lists and an FAQPage block.
  • The glossary page has 10 numbered H2 sections and a FAQPage block.
  • /news has 3 H2s and 19 H3s.
  • The /news H1 merges the site name and tagline ("Signal Observatory What changed in search and AI this week").
  • Retriever issues: the 7 dangling-section pages, 67 walls of text and 21 low-main pages above all affect how well a passage can be quoted on its own.

What I did not cover

  • Crawl size: you asked for 500 URLs if no crawl was open. Crawl #32 was open, so I used it. It has 300 URLs and its limit was 300, so any URLs beyond that are missing. The crawl date was not in the tool results.
  • Probe: about 10 pages per bot. Five training bots were checked in robots.txt only.
  • Fix list: it returned 33 fixes, which is the full list. I did not call explain_fix or get_fix_urls, so the URL lists per fix are not shown.
  • Not counted: jsContent, javascript.* and noInlinks are not in the fix list.
  • Embeddings: all 300 pages have embeddings. I did not use topics, cannibalization detail or semantic search.
  • Not run: Search Console data and Markdown tests beyond 3 URLs. No tool failed.
  • Report: I did not save it with save_report.

B3Preparación de una página para agentes

Antes de lanzar una página clave de aterrizaje, registro o precios.

/page-agent-readiness*
1 herramienta

Herramientas de GLLmolfar que llama: audit_url

Rellenas: url

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026, texto de la habilidad de 0.8.1 · 33 s · 2 llamadas a herramientas de GLLmolfar · sin editar, en inglés

URL audit of https://www.getlooploop.com/

Source for everything below: URL audit, 2026-10-28 14:04 UTC (HTTP 200, indexable). No crawl was running when I checked, so I ran the audit. I did not call crawl 32 or any other tool. Where a line is my own reading, I mark it as judgment.

The 3 most important changes

  1. Fix the aria-label on the glossary graph link (.home-graph-preview). Its accessible name does not contain its visible text. This is a names-and-labels fix (WCAG 2.5.3).
  2. Fix the <dl> markup in .home-kpis. One block of markup causes two serious violations, definition-list and dlitem.
  3. Raise the colour contrast on .shadow-sm > .sm\:inline.hidden (the "Light" theme label) and .home-moved-axis--window. After the change, run the URL audit again.

1. axe-core violations (impact critical or serious)

Source: URL audit, axe-core 4.14.0. There are no critical violations. There are 4 serious ones. Corrections follow your sequence.

Names and labels

RuleSelectorCorrection
label-content-name-mismatch.home-graph-preview (<a href="/glossary/graph" aria-label="Explore the marketing glossary knowledge graph">)Make the aria-label start with the link's visible text, or remove the aria-label. (judgment: the audit does not list the visible text, so I can't give the exact string)

Content without JavaScript (markup served in the HTML)

RuleSelectorCorrection
definition-list.home-kpis (<dl>)A <dl> may directly contain only <dt>/<dd> groups, <div>, <script> or <template>. Make the wrapper that holds the dt/dd a <div>.
dlitem (4 nodes).home-kpi-moved-head > .home-kpi-label, .home-kpi-moved-head > .home-kpi-value.home-kpi-value--lg, .home-kpi-moved-head > .home-kpi-note, dd:nth-child(4)Each <dt>/<dd> must sit inside a <dl>. This should clear once .home-kpi-moved-head is a <div> directly inside .home-kpis, or the <dt>/<dd> elements are restructured to match.

All other items

RuleSelectorCorrection
color-contrast (2 nodes).shadow-sm > .sm\:inline.hidden (<span class="hidden sm:inline">Light</span>), .home-moved-axis--windowRaise the text/background contrast to at least 4.5:1 (WCAG AA). The audit does not give the measured ratios.

2. What JavaScript changes

Source: URL audit (raw HTML compared with the rendered page).

  • Title, canonical, meta robots: the audit reports no difference. Title is "GetLoopLoop — AI Visibility Tracking for ChatGPT & Gemini". Canonical is https://www.getlooploop.com/. Meta robots is index, follow. The audit lists only links under jsDiff.
  • Links: 2 differ. The rendered text adds "Sign in" and "Start" in the header, and they are absent from rawText. (judgment: these are the 2 links the audit counts.)
  • Word count: 1931 raw and 1931 rendered, so no difference. The rendered HTML is 754 bytes larger (273,632 raw, 274,386 rendered).
  • Not covered: the audit gave no list of which links changed beyond the count.

3. Prices, plan limits, contact data, testimonials

Source: URL audit, rawText and renderedText.

ItemResult
PricesNo price text in rawText or renderedText. JSON-LD has Offer price 0 USD, "Invite-only access".
Plan limitsNo plan limits in either text. Free-tool limits are in both: "One URL at a time", "One keyword at a time", "Up to 4 000 words".
Contact dataThe audit found no phone numbers and no emails. Only "Request an invite", "Write" and "Discord" appear, in both rawText and renderedText.
TestimonialsNone in rawText or renderedText.

Other findings:

  • Schema error: the audit flags SoftwareApplication.aggregateRating|review. The visible page has no testimonials or ratings to back it.
  • Schema warnings: Offer.url and ListItem.item.
  • The JSON-LD in the audit output was cut off, so I did not check the whole block.
  • Everything else in the sections above is in both rawText and renderedText.

4. robots.txt per AI bot

Source: URL audit. robots.txt was found. Every bot is allowed by Allow: / in group * (line 2).

BotAllowedWhat it controls
GooglebotyesGoogle Search and AI Overviews
OAI-SearchBotyesChatGPT search
GPTBotyesOpenAI training only
ClaudeBotyesAnthropic training only
Google-ExtendedyesGoogle training only
PerplexityBotyesPerplexity

The audit did not include Claude-SearchBot, so I have no result for Claude search.

5. Does the response change with the Accept header?

I did not test this. The audit tool sends one request and has no Accept-header option, and I have no other tool to send a custom request. The only hint is the vary header: rsc, next-router-state-tree, next-router-prefetch, next-router-segment-prefetch. It does not list Accept. That suggests the HTML does not change by Accept, but it only shows what the server declares, not what it does. To verify, request the page with Accept: text/markdown and Accept: text/html and compare.

Not covered

  • Accept-header test (above).
  • Claude-SearchBot robots result.
  • Visible text of the glossary graph link and measured contrast ratios (the audit did not return them).

Appendix: other findings from the same audit

  • axe region (moderate, 5 nodes): targets .pb-20, .home-eyebrow.text-gll-cyan and others in the hero. Put the hero content inside a landmark such as <main>.
  • Images: 22 of 30 have no alt text.
  • Sitemap: the page is not in the sitemap (inSitemap: false).
  • Cache-Control: private, no-cache, no-store.
  • Open axe items: 2 "incomplete" results that need manual review.

B4Citabilidad y plan de reescritura de una página

Una página que debería citarse para ciertas preguntas y no se cita.

/citability*
3 herramientas

Herramientas de GLLmolfar que llama: semantic_searchaudit_urlmeasure_text

Rellenas: url, questions

Ver una respuesta real

Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026, texto de la habilidad de 0.8.1 · 57 s · 6 llamadas a herramientas de GLLmolfar · sin editar, en inglés

AI Visibility glossary page: review and rewrite of two sections

Page: https://www.getlooploop.com/glossary/ai-visibility Sources: crawl 32 (https://www.getlooploop.com/, 300 URLs, limit 300, embeddings on) and a URL audit run on 28 Oct 2026 at 14:05 UTC. Judgments are marked (judgment).

The most important changes

  1. Answer "why does ChatGPT not mention my brand" on the page itself. (judgment) The page has no section for it. The only related text is the first "Asked out loud" answer, which begins with "Yes" to a question that is not yes/no. The draft in the rewrite below fits this question at 0.788, against 0.471 for the current page.
  2. Rewrite section 03 so it can be measured and sourced. (judgment) It has no number, no named bot and no steps. The draft raises the fit for "how do I measure my brand in ChatGPT answers" from 0.553 to 0.717.
  3. Move the measurement section up. (judgment, not measured) On the current page it is the 4th passage. The draft only tested the new text in isolation, so I cannot confirm that moving it improves retrieval.

1. Semantic search on crawl 32

QuestionBest pageScoreIs the target first?
What is AI visibilityThe target page, section "GetLoopLoop"0.603Yes (next is /brandscope at 0.498)
How do I measure my brand in ChatGPT answers/brandscope0.608No. The target is 5th at 0.479.
Why does ChatGPT not mention my brand/brandscope0.599No. The target is 3rd at 0.488.

The search returned only one section per page (the top section, mostly the intro). I could not see the page's own section scores there. For section-level scores I used measure_text.

2 and 3. Section audit

Source: URL audit, 28 Oct 2026, rendered text of 1,006 words. Judgments are (judgment).

SectionFirst sentence answers directly?Names its subject?Specific, sourced fact?Stands alone?
IntroYes. It defines the term.YesNo. The only source is the "Google Search Central" label.Yes
01 What it isNo. It describes how search tools work and defines the term only in the last sentence.Partly. It ends with "It is how often…".No. "Relevance, authority" are named without evidence.No, because of "It" at the end
02 What to doYes (a list)YesWeak. "At least three backlinks" has no source.Yes
03 How it is measuredPartly. "No public score" is true but is not a method.YesNo. It names Google AI Search, Copilot and Search Console without a figure or date.Yes
04 Common mistakesYesYesNo. No source.Yes
05 LimitsYesYesNoNo ("It is also different…")
06 Worked examplen/a (an anecdote)"BrandX", an invented brandNo. It is not verifiable.Yes
07 FAQ (6 items)Mostly. Some start "It is not the same" or "Usually".MixedNo sourcesYes
08 Asked out loud (3)No. "Yes, the AI may not…" answers a non-yes/no question. "No, the AI isn't ignoring…" is also unclear.NoNoYes
10 Sourcesn/an/aOne link only, no datesn/a

Other findings from the audit:

  • The audit's headings list shows 10 H2 sections plus H3s. Zero headings are phrased as questions (questionHeadings = 0).
  • All six bots checked (Googlebot, GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot, Google-Extended) are allowed by "Allow: /glossary".
  • The page has no author or dateModified in its structured data, and no statistic sentences (statSentences = 0).

4. Rewrite plan by section

  • Intro: keep as is. It is the page's strongest passage for question 1.
  • 01: open with the definition, name "AI Visibility" in the last sentence in place of "It", and source one claim.
  • 02: add the source or reason for each action.
  • 03 (rewritten below): lead with the method, name the metrics, source the facts.
  • 04: attach one source per mistake.
  • 05: replace "It is also different" with the subject name.
  • 06: replace BrandX with a real, dated, sourced case.
  • 08 (rewritten below): start with the cause and name OAI-SearchBot.

5. Rewrites of the two weakest sections

Both sections keep the page's plain-English glossary voice.

03 How to measure AI Visibility in ChatGPT answers

To measure AI Visibility in ChatGPT, ask ChatGPT the questions your buyers ask, then count how many answers name your brand and how many cite your URL. AI Visibility has no public score, so the measure is your own count: brand mentions divided by questions asked, repeated on the same list of questions each week.
Use three readings, and keep them apart:
- Mentions: the share of ChatGPT answers that name your brand. Ask five to ten buyer questions and record yes or no for each.
- Citations: the share of answers whose source list includes a URL of your domain.
- Search Console: Google Search Console shows impressions and clicks for Google Search only. It does not show ChatGPT answers.
Brandscope, a free GetLoopLoop tool, puts five buyer questions to ChatGPT, Claude and Gemini and shows each answer beside your own page. Run the same questions again after every change to your pages, because a citation can fade within days (GetLoopLoop market analysis, 16 October 2026).

08 Why ChatGPT does not mention my brand

ChatGPT does not mention your brand when its search crawler cannot fetch your pages, or when no page of yours answers the question in a passage it can quote. Check these three causes in order.
1. Access. OAI-SearchBot is the crawler that controls ChatGPT search. If robots.txt disallows OAI-SearchBot, ChatGPT search cannot read your pages. GPTBot controls training only and does not decide this. On getlooploop.com, the URL audit of 28 October 2026 shows OAI-SearchBot allowed by "Allow: /glossary".
2. Answer. A page must state the answer in its first sentence and name the brand in it. A page that says "it" or "this" gives the model nothing to quote.
3. Competition. The model may prefer a competitor's page that matches the question better. Compare your best passage with theirs for the same question.
To verify a change, ask ChatGPT the same question again after the page is re-crawled, and run the URL audit again to confirm OAI-SearchBot is still allowed.

6. measure_text results (draft against the current page)

The draft contained only the two new sections (345 words, 2 passages). The current page has 10 passages.

CriterionQuestion 2 (measure)Question 3 (why not mentioned)Verdict
Fit, current → draft0.553 → 0.7170.471 → 0.788Higher for both
Position of the answer4th → 1st in the draft2nd → 2nd in the draftNot shown. The draft has only 2 passages, so its position says nothing about the full page.
New overlapNearest page is /brandscope at 0.77, below the 0.94 cannibalization lineSameNone. The current page's nearest page is /glossary/ai-overview at 0.766.
Passages that need an earlier passage0 (dangling = 0)0OK

The tool also reported "fit-lower". That is for question 1 ("what is AI visibility"): 0.607 on the current page, 0.454 in the draft. I did not rewrite the passage that serves that question, so section 01 and the intro stay in place. (judgment)

Decision (judgment):

  • Keep both rewrites. The fit is higher for questions 2 and 3, and there is no new overlap.
  • The "answer in an earlier passage" test is not met. Moving section 03 higher on the real page is a recommendation that has not been measured.
  • Re-run measure_text with the full revised page, not only the two sections, to get a real position and an overall fit before publishing.

Not covered

  • Section scores for the target page in semantic search. The search returned one section per page, so I used measure_text for per-passage scores.
  • Crawl size. Crawl 32 has 300 URLs (limit 300), and every URL has an embedding. It is a single crawl from 28 Oct 2026, with no comparison to earlier crawls.
  • Not run: Search Console data (not available), and ChatGPT itself. Nothing here shows what ChatGPT answers today.
  • Facts used in the draft that need checking before publishing.
  • The statement that a citation fades within days comes from the title and subtitle of a GetLoopLoop page in the crawl ("citations fade in 11 days"). I did not read the full article.
  • "Five to ten questions" is my suggestion, not a sourced figure.
  • Pages I did not measure: neighbouring pages (/brandscope, /glossary/ai-overview) beyond their nearest-neighbour scores.

Verifying after publishing

  1. Run the URL audit on the page again to confirm the new text is served and OAI-SearchBot is still allowed.
  2. Re-run the three semantic searches in a new crawl.
  3. Run measure_text on the full page. The changes unblock a clearer answer for retrieval. They do not promise citations, rankings or traffic.

B5Prueba de cobertura de preguntas (fan-out)

Planificar contenido sobre un tema: ¿qué preguntas no responde el sitio?

/question-coverage*
1 herramienta

Herramientas de GLLmolfar que llama: semantic_search

Rellenas: topic, audience, brand

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026, texto de la habilidad de 0.8.1 · 167 s · 33 llamadas a herramientas de GLLmolfar · sin editar, en inglés

I'm summarising 30 semantic searches on the loaded crawl and writing the report. Crawl 32 was already open and no crawl was running, so I started nothing.

AI visibility tracking: coverage check for getlooploop.com

Sources. [C32] means semantic search on crawl 32 (28 Oct 2026, about 13:33 UTC, 300 pages, all 300 embedded). [J] means my judgment. I did not use URL audit or Search Console.

The 3 changes that matter most

  1. Answer "What is GetLoopLoop?", "vs Profound", "alternatives" and "price" in one place (Q27, Q29, Q12, Q30).
  2. [C32] For "What is GetLoopLoop?" the best page is /legal/terms (0.547), and the homepage is not in the returned list. For "GetLoopLoop vs Profound" the best page is again /legal/terms (0.441).
  3. [J] Add a "What GetLoopLoop is" block to the homepage. Add one comparison page that covers both "vs Profound" and "alternatives". Add a "What is free, what costs money" page.
  4. What this unblocks: a retriever finds a page that answers a brand question, instead of a legal page that only matches the name. Verify: run the same four questions on the next crawl.
  1. Add one page on AI bot access (Q4, Q19, Q22).
  2. [C32] Best scores are 0.516, 0.474 and 0.479, and none has a clear leader. For "Which AI crawlers read my site?" the top page is /glossary/ai-referral-traffic.
  3. [J] Write "Which bot controls which assistant", with one claim per bot: OAI-SearchBot controls ChatGPT search, Claude-SearchBot controls Claude search, Googlebot controls Google Search and AI Overviews. GPTBot, ClaudeBot and Google-Extended are training only. Add a how-to section for each of OAI-SearchBot and Claude-SearchBot.
  4. What this unblocks: a page whose text answers the crawler questions. Verify: re-run the three questions on the next crawl. To check your live robots.txt, run get_ai_readiness or audit_url, which I did not run.
  1. Add one "how to choose" page for the choose-intent questions (Q11, Q13, Q14, Q17, Q18).
  2. [C32] Every one of these has a best score of 0.442–0.521 and a gap under 0.05. /brandscope or /glossary/ai-visibility is top or second in 3 of the 5.
  3. [J] Write one hub page: how to choose an AI visibility tool. Sections: AI visibility tracking vs rank tracking, crawl audit vs prompt sampling, suite SEO tool vs specialised tool, and a small-team path.
  4. What this unblocks: a page that matches comparison questions. Verify: re-run the five questions on the next crawl.

One duplicate to fix.

  • [C32] For Q16, /glossary/ai-overview (0.568) and /glossary/ai-overviews (0.562) are 0.005 apart.
  • [J] These look like two pages for one topic. Merge them or canonicalise one to the other, then run GLLmolfar's cannibalization view to confirm.

How I decided "clearly"

All numbers are [C32].

  • Best scores run from 0.441 to 0.670, a spread of 0.229. The median best score is 0.55.
  • Gaps (best minus second) run from 0.002 to 0.266. The median gap is 0.024.
  • Clearly above = gap of 0.05 or more. That is about the top quartile of gaps and about a fifth of the spread.
  • A (coverage gap) = gap under 0.05 and best score below 0.55. That is 14 questions.
  • Overlap (o) = gap under 0.05 and best score at or above 0.55. Several pages answer, none leads. That is 8 questions.
  • B (cannibalization) = top two are both our pages, within 0.010, on the same intent. That is Q16 and Q30.
  • C (answer only in section 3 or lower) could not be tested. The tool returned one section per page, section 1 for all 30, so no question is flagged. Deeper sections may exist but were not scored.

Eight questions have a clear leader: Q2, Q8, Q9, Q15, Q24, Q25, Q26 and Q28.

Appendix 1: all 30 questions [C32]

Section is §1 for every row. L = learn, C = choose, T = task, B = brand. "Home" is the homepage /.

#QuestionBest pageScoreSecond pageGapFlag
1 LWhat is AI visibility tracking for brands?/glossary/ai-visibility0.639/brandscope 0.6240.015o
2 LHow do AI assistants decide which brands to mention?/news/brands-in-ai-answers-october-2026…0.670/brandscope 0.5530.118clear
3 LSEO vs generative engine optimization?/glossary/generative-engine-optimization0.553/skills/…/seo-image-gen 0.5100.043o
4 LWhich AI crawlers read my site?/glossary/ai-referral-traffic0.516/glossary/ai-cloaking 0.5130.003A
5 LHow does robots.txt affect AI search visibility?/glossary/ai-visibility0.568/glossary/robots-txt 0.5550.014o
6 LWhat metrics measure brand visibility in AI answers?/brandscope0.651/glossary/ai-visibility 0.6270.024o
7 LHow do AI assistants split pages into passages?/vectorscope/claude-skill0.505/glossary/ai-assistant 0.5020.003A
8 LWhy is my brand not in ChatGPT answers?/brandscope0.589/news/brands-in-ai-answers… 0.5270.062clear
9 CBest AI visibility tracking tools/brandscope0.622/glossary/ai-visibility 0.5610.061clear
10 CBest tools to track mentions in ChatGPT and Perplexity/brandscope0.552Home 0.5330.020o
11 CAI visibility tracking vs rank tracking/glossary/ai-visibility0.521/brandscope 0.4810.040A
12 CAlternatives to Profound/brandscope0.451/glossary/ai-visibility 0.4190.032A
13 CBest GEO tools for marketing teams/glossary/generative-engine-optimization0.441/skills/…/seo-image-gen 0.4170.024A
14 CCrawler audit vs prompt sampling/glossary/ai-audit0.477/skills/firecrawl/…/firecrawl-seo-audit 0.4410.036A
15 CFree AI visibility checker/brandscope0.634/notes/ai-reads-your-page… 0.5280.106clear
16 CMonitor citations in Google AI Overviews/glossary/ai-overview0.568/glossary/ai-overviews 0.5620.005o, B
17 CBest AI search platform for a small business/skills/coreyhaines31/…/ai-seo0.442/notes/ai-reads-your-page… 0.4180.024A
18 CSemrush vs specialised AI visibility tools/glossary/ai-visibility0.487/brandscope 0.4640.023A
19 TCheck if my site is blocked for ChatGPT search/news/chatgpt-s-clicks-now-arrive-as-direct-traffic0.474/brandscope 0.4400.035A
20 TAudit a page for AI search readiness/glossary/ai-audit0.625/notes/ai-search-audit-full… 0.6050.020o
21 TTrack my brand mentions in AI answers/news/brands-in-ai-answers…0.575/brandscope 0.5730.002o
22 TAllow OAI-SearchBot and Claude-SearchBot in robots.txt/glossary/robots-txt0.479/vectorscope/claude-skill 0.4680.011A
23 TFind content gaps AI cannot answer from my site/notes/ai-reads-your-page…0.486/skills/…/content-gap-analysis 0.4660.020A
24 TRewrite a page so AI can cite it/glossary/citation0.506/notes 0.4470.059clear
25 TCreate an llms.txt file/glossary/llms-txt0.573/glossary/ads-txt 0.3220.251clear
26 TReport AI visibility to management/glossary/ai-visibility0.591/glossary/ai-overview 0.5090.082clear
27 BWhat is GetLoopLoop?/legal/terms0.547/glossary/agent-loop 0.5390.007A
28 BWhat is GLLmolfar?/gllmolfar0.577/glossary/llms-txt 0.3110.266clear
29 BGetLoopLoop vs Profound/legal/terms0.441/gllmolfar 0.4310.010A
30 BIs Vectorscope free, and what does it cost?/notes/vectorscope-as-an-agent-skill…0.504/vectorscope 0.4970.007A, B

Patterns [C32].

  • /glossary/ai-visibility or /brandscope is the top page for 11 of 30 questions.
  • At 0.670, the strongest match in the whole run is only moderate.

Close calls [J].

  • Q21 (0.002 gap) is a news analysis against a tool page. I read that as overlap, not cannibalization.
  • Q5, Q1 and Q22 have gaps of 0.014, 0.015 and 0.011, just outside the tie band.

Appendix 2: proposals for the 14 coverage gaps [J]

Where one page serves several questions, I merged them to avoid creating new cannibalization.

QuestionsProposal
Q4, Q19, Q22One new page, "Allow ChatGPT and Claude search to read your site". It opens with the bot table from change 2. It has a check section for OAI-SearchBot and a robots.txt snippet section for each of OAI-SearchBot and Claude-SearchBot. It links to the existing robots.txt glossary page.
Q7New first section on /glossary/chunking: "How a retriever cuts your page into passages", with the 26-passage cap and one example. Link to Vectorscope.
Q11, Q13, Q17, Q18One hub page, "AI visibility tools: how to choose". It has sections: vs rank tracking, suite vs specialised, GEO tools for marketing teams, small-team path.
Q14New section on /gllmolfar and the hub: "Site crawl vs prompt sampling: what each can and cannot show".
Q12, Q29One new comparison page, "GetLoopLoop vs Profound, and other alternatives". Competitor facts must come from verified sources.
Q23New how-to page or section: "Find content gaps with semantic search on a crawl". It describes the method used in this report.
Q27New "What GetLoopLoop is" block at the top of the homepage: what it is, who it is for, what it measures.
Q30New "What is free, what costs money" page. Also decide which of /vectorscope and the Vectorscope note owns the question, to resolve the B flag.

Not covered

  • URL limit. Crawl 32 stopped at its 300-URL setting with nothing queued. Earlier crawls (25, 27) reached 500 pages, so some pages are not in this run.
  • Lists cut. Each search returned a list of about 20–30 pages. I recorded only the top two per question.
  • Sections. The tool gave one section per page, so criterion C is untested.
  • Pages without embeddings. None; 300 of 300 are embedded.
  • Tools not used. I did not run get_ai_readiness, audit_url, get_fixes, Search Console or the cannibalization view. Your live robots.txt is unverified.
  • Tool failures. None.
  • Questions. All 30 are my own, not real prompt data. I chose the competitors Profound and Semrush myself, so please confirm them.

I can also turn this into a shareable page if you want to send it to your team.

B8Borrador de llms.txt

El sitio quiere un llms.txt o GLLmolfar encontró problemas en el actual.

/llms-txt*
4 herramientas

Herramientas de GLLmolfar que llama: get_topicsget_pagessemantic_searchget_ai_readiness

Rellenas: site

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026, texto de la habilidad de 0.8.1 · 62 s · 12 llamadas a herramientas de GLLmolfar · sin editar, en inglés

Google does not use llms.txt. The file is for other agents and tools.

The draft is saved at (work folder)\llms.txt. It has 26 link lines under 9 H2 sections.

Most important points

  1. A live llms.txt already exists (AI readiness probe, 2026-10-28): 33 KB, 32 links, 15 sections, 0 broken links. Compare this draft with it before you replace it. This draft is shorter, with 26 links.
  2. No about, pricing, documentation or contact page is in crawl 32. The page table has no URL for any of them. They are left out, not guessed. The Home page is included. I added a "Site" section for it, plus methodology, questions and legal, which you did not ask for.
  3. Most topics are clusters of agent-skill pages and glossary terms. There are no guide pages for these topics. For "Workflows published" and "Technical SEO" I used the /skills hub and the highest-scoring skill page. For "Ad affiliate" and "Testing variance" the best matches are weak. The scores are 0.52 and 0.37 for Ad affiliate, and 0.52 for Testing variance. Check these two sections by hand.

Sources

  • Crawl 32 (open crawl, 300 pages, embeddings on): topics, semantic search, and the pages table. I kept 294 pages that are status 200, indexable and have a canonical to themselves. Every URL in the draft is among them. Each line comes from that page's title, H1 and description, with no marketing claims added.
  • AI readiness probe (2026-10-28): the current llms.txt data above.
  • My judgment: which page best shows each topic.

AI access

  • OAI-SearchBot, Claude-SearchBot and PerplexityBot: robots.txt allows all paths, and 10 of 10 test pages were fetched without problems.
  • Googlebot was not tested.
  • llms.txt does not unblock any bot. To check changes, run get_ai_readiness again with run_probe.

What I did not cover

  • Crawl 32 stopped at its 300-page limit, so pages beyond it are not in the draft.
  • I ran one semantic search per topic and took only the top results. I did not check each topic's other pages.
  • The 6 pages that are not status 200, not indexable or not self-canonical are excluded. I did not list them.
  • The topic names are GetLoopLoop's cluster labels (such as "Ai getlooploop"). I used them as H2 headings with light capitalization. Rename them before you publish.

Appendix: pages per topic

TopicPages in the crawlLines in the draft
Workflows published1012
Technical SEO551
Ai getlooploop534
Ad affiliate332
Ai news304
Vectorscope ai125
Text robots102
Testing variance51

The "Site" section adds 4 more lines.

* Cómo se ven los comandos de barra, y si aparecen, depende del agente que conectes, no de GLLmolfar. Copiar el texto funciona en cualquier agente.

** Aún sin ejemplo: esta habilidad necesita el repositorio del sitio, el sitio de un competidor o una herramienta de Search Console en el agente.

Ideas adaptadas de habilidades abiertas de SEO, GEO y AEO (MIT y Apache-2.0); todos los textos están escritos para GLLmolfar en inglés técnico simplificado.

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