Rastrea el sitio.
Entiende las páginas.
Sabe qué corregir.

GLLmolfar combina un rastreo SEO técnico con un análisis semántico opcional en tu propio equipo. Revisa sus URL, mira cómo pueden leerlas los rastreadores y asistentes de IA, sigue cada hallazgo hasta las páginas que lo causan y decide qué merece atención.

Al descargar aceptas los términos de la preview de GLLmolfar.

118descargasVer el vídeo
Aún sin firmar Windows y macOS mostrarán un aviso. Cómo ejecutarla o comprobar el archivo
Preview 0.9.23 Windows 10+ · macOS (Apple silicon) 50.000 URL por rastreo, gratis con una cuenta** Embeddings locales opcionales

** 5.000 URL sin cuenta, 50.000 con una cuenta gratuita, hasta 1.000.000 en los niveles de pago. Así funciona ahora: es una intención, no una promesa; los límites pueden cambiar y cambiarán.

* Se actualiza una vez cada 24 horas.

ResumenCaptura · 0.9.23
Un rastreo de getlooploop.comApp real, rastreo real.
Una página web descompuesta en sus bloques de texto e imágenes, cada uno unido a la página por una línea; debajo, PREVIEW, NOT A RELEASE

Una vista previa, no una versión final.

GLLmolfar ya rastrea sitios reales y encuentra problemas reales, pero aún está en construcción. Úsala y cuenta con que cambiará.

  • Las funciones, los límites y los formatos de archivo pueden cambiar de una versión a otra.
  • Algo puede fallar. El botón Opinión de la app nos envía un informe con captura y, si lo dejas marcado, un registro de diagnóstico con recuentos y errores, sin direcciones ni texto de páginas; la respuesta vuelve a la app.
  • Las versiones aún no están firmadas, así que Windows y macOS avisan antes del primer inicio.
  • Tus rastreos se quedan en tu equipo, cambie lo que cambie.
Qué cambió en la última vista previa

Todavía no hay certificados de firma, ni para Windows ni para Mac.

Windows y macOS avisan de cualquier app que no esté firmada con un certificado de pago de Microsoft o Apple. GLLmolfar aún no tiene esos certificados, así que verás el aviso. Tienes tres opciones.

  1. Confiar y ejecutar

    En Windows: Más información y luego Ejecutar de todas formas. En Mac: Ajustes del Sistema, Privacidad y seguridad y luego Abrir igualmente.

  2. Comprobar el archivo antes

    La ventana de descarga muestra el SHA-256 del archivo. Compáralo con el archivo descargado: el mismo valor significa que es exactamente el archivo que publicamos.

    Windows: certutil -hashfile <archivo> SHA256Mac: shasum -a 256 <archivo>
  3. Esperar a las versiones firmadas

    Compraremos los certificados antes del lanzamiento completo. Marca «Avísame por email cuando salga una versión nueva» en el formulario y te avisaremos cuando estén listas.

Un espacio de trabajo de escritorio paraSEO técnicoEquipos de contenidoConsultores independientesPropietarios de sitios

MIRA · 2 MIN 24 S

Un agente. Un rastreador.
Toda la auditoría.

Conecta Claude Code, Codex o cualquier agente MCP y manejará GLLmolfar por ti: lanza el rastreo, lee los hallazgos y vuelve con un plan. Elige un capítulo para ir directo a él.

El vídeo está en inglés y su sitio y sus cifras son de demostración. ** Los límites de URL por nivel de cuenta están al principio de esta página: una intención, no una promesa, y cambiarán.

GLLmolfar manejado por un agente de IA por MCP · vista previa

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.

NUEVO EN 0.8.1

Qué hay de nuevo
desde la última preview.

Todo lo de abajo ya está en la app. Lo marcado como prueba vive en la sección Agente · prueba de la app y puede cambiar.

FunciónQué haceDónde
Habilidades del agente18 trabajos listos de SEO, GEO y AEO para tu agente de IA, con su texto completo para copiar.Ayuda › Habilidades del agente; prompts MCP
Tabla de páginas para agentesTu agente lee cualquier columna de cualquier página y cuenta páginas por estado, profundidad, tema, carpeta, plantilla o problema.MCP: get_pages, count_pages
Preparación para IA para agentesLa puntuación de preparación para IA con sus partes, robots.txt por bot de IA, llms.txt y Markdown para agentes.MCP: get_ai_readiness
Comparación de rastreos para agentesPáginas encontradas y perdidas, y por qué; qué mejoró o empeoró; bots de IA bloqueados de nuevo.MCP: compare_crawls
Medición de borradoresMide un borrador frente a tu sitio con embeddings, en tu ordenador, sin modelo de lenguaje: dónde está la respuesta, cuánto encaja con las consultas, si se solapa con otra página.MCP: measure_text
Tus propios modelos de IApruebaConecta Ollama, LM Studio, OpenRouter, OpenCode Zen, LiteLLM o cualquier servidor compatible con OpenAI, y elige qué modelo hace cada trabajo.Ajustes › Modelos de IA
Agente: plan, contenido, publicacionespruebaUn plan de tareas comprobado con el rastreo; reescrituras medidas y repetidas hasta que pasan; publicaciones para X, LinkedIn, Threads, Bluesky y más.Agente · prueba
Contenido de riesgopruebaEncuentra contenido para adultos, farmacia, apuestas, estafas, falsificaciones y drogas e inyecciones de atacantes; tu modelo juzga solo lo encontrado.Agente · prueba › Riesgos
AccesibilidadComprobaciones de axe-core en la auditoría de URL, sobre la página renderizada.Auditoría de URL
Markdown para agentesComprueba si el sitio sirve Markdown a los agentes que lo piden.Pestaña IA
Alertas tras rastreos programadosDice qué empeoró desde el rastreo anterior: salud, problemas nuevos, bots de IA bloqueados en robots.txt.Rastreos programados

Tus modelos funcionan donde los conectas; GLLmolfar no nos envía nada. Los límites de la app son una intención y cambiarán.*

Mira lo que hace el rastreador
en cada paso.

Un rastreo es un conjunto de peticiones y respuestas registradas. GLLmolfar deja a la vista el descubrimiento, la extracción y el análisis opcional de significado, para que entiendas cómo se generó el informe.

01

Elige el punto de partida

Introduce un dominio o la URL de una sección. Elige Spider + sitemap, solo Spider, solo Sitemap o una lista de URL para revisar.

02

Define los límites del rastreo

Fija un límite de páginas y, si hace falta, profundidad, patrones de inclusión o exclusión, tratamiento de parámetros, subdominios, ritmo de peticiones, conexiones paralelas y cabeceras.

03

Sigue dos colas

El rastreador descubre y descarga páginas. El análisis opcional de embeddings va en su propia cola local. La vista general muestra cada etapa en directo, con páginas por segundo de descarga, renderizado y embeddings en un gráfico, así puedes pausar el rastreo o desactivar los embeddings.

04

Del hallazgo a sus URL

Empieza en el resumen o en la lista de correcciones, abre las filas afectadas y revisa el código de la página, los enlaces, las directivas, los fragmentos o las páginas que compiten.

Cómo entran las URL en el rastreo

Por defecto

Spider + sitemap

Descubre enlaces internos desde la URL inicial y lee los sitemaps XML del sitio. Compara las páginas alcanzadas por enlaces con las listadas en el sitemap.

Por enlaces

Solo Spider

Sigue los enlaces internos desde la URL inicial. Útil para ver qué expone la estructura de navegación del sitio.

Por sitemap

Solo Sitemap

Reúne URL de los sitemaps XML sin recorrer enlaces internos. Útil para una revisión guiada por el sitemap.

Revisión puntual

Lista de URL

Pega o importa una lista conocida de URL para revisar páginas concretas. Este modo no descubre el sitio siguiendo enlaces.

Señales técnicas,
con su origen.

Abre un hallazgo y pasa del resumen a las URL afectadas y, de ahí, a la evidencia de cada página: enlaces, cabeceras, código y campos extraídos.

Accesibilidad e indexación

Estado HTTP y tiempo de respuesta, cadenas de redirecciones, acceso según robots.txt, meta robots, X-Robots-Tag, destinos canonical, presencia en el sitemap, profundidad de rastreo y señales de páginas huérfanas.

Estructura de la página

Títulos y su ancho en píxeles, meta descriptions, encabezados H1/H2, número de palabras, valores duplicados, contenido duplicado exacto y texto que solo aparece tras renderizar JavaScript.

Enlaces y recursos

Enlaces internos y externos, entrantes y salientes, texto ancla, URL rotas, enlaces a redirecciones, enlaces nofollow, imágenes y alt ausente.

Detalles técnicos

Hreflang, datos estructurados y validación de JSON-LD, cabeceras de seguridad y de respuesta. La revisión opcional de enlaces externos pide cada URL externa encontrada una sola vez.

Respeta las reglas de rastreo del sitio. robots.txt se respeta por defecto, y un Crawl-delay más lento prevalece sobre el ritmo configurado. Los presets de bots como Googlebot o GPTBot siempre cumplen el grupo de robots.txt de ese bot, en un rastreo y en una sola página, y un user agent propio no puede usar el nombre de otra empresa. Durante el rastreo, la app muestra su agente y tu dirección pública, para que el dueño del sitio encuentre estas peticiones en sus registros. Un 429 o 503 se reintenta tras el Retry-After del sitio y el rastreo se ralentiza. Si un sitio responde con un CAPTCHA, el rastreo se pausa y abre la página para que lo superes, y luego sigue con el acceso concedido; los rastreos programados nunca lo esperan, y un interruptor en Ajustes › Rastreo desactiva la pausa.

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.

Problemas y lista de correcciones

Las comprobaciones se agrupan por importancia y tipo. Cada hallazgo muestra las URL afectadas, su proporción entre las filas revisadas, por qué importa y qué revisar o cambiar. La puntuación de salud del sitio resume comprobaciones ponderadas; no es una puntuación de Google ni una previsión de posiciones. Abre el conjunto exacto de URL, expórtalo o exporta el hallazgo como informe PDF.

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.

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.

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.

Historial e informes

Vuelve a abrir rastreos locales y compara entre ejecuciones URL, estados, títulos, descripciones, encabezados, indexación, canonical y significado del contenido. Exporta un informe para cliente, para desarrollo o uno breve, en HTML o PDF.

Estructura y correcciones en lote

Mira el sitio como árbol de rastreo, árbol de directorios o grafo de fuerzas. Las correcciones en lote agrupan los hallazgos que resuelve un solo cambio —en todo el sitio, por plantilla o por tema—, así corregir una plantilla no cuenta como cuatrocientas tareas.

Auditoría de URL

Revisa una página sin rastreo: la app la descarga, la renderiza con JavaScript, hace capturas de escritorio y móvil y ejecuta las comprobaciones de página. Cada comprobación fallida trae su corrección. Las comprobaciones de todo el sitio, como enlaces entrantes y duplicados, siguen necesitando un rastreo.

Proyectos

Una tarjeta por cada sitio rastreado: la salud y su tendencia, páginas, errores, páginas no indexables y temas, comparados con el rastreo anterior. La tarjeta también lee robots.txt, el sitemap y el registro del dominio: antigüedad, caducidad, registrador, servidores de nombres, correo y DNSSEC.

Google Search Console

Conecta la cuenta de Google con la que inicias sesión, solo lectura, y Search Console se convierte en una sección de nueve informes: rendimiento frente al periodo anterior, páginas con su consulta principal y su estado en el rastreo, consultas por tramos de posición, el veredicto de indexación de Google página a página, sitemaps, clics perdidos con su causa probable, consultas repartidas entre tus páginas, grupos de consultas y una visualización. Los datos van de Google directamente a la app, se quedan en tu equipo y siguen ahí, con su fecha, sin conexión o sin sesión.

Agentes de IA y prompts inversos

Con la sesión iniciada, activa el servidor MCP local de la app y Claude Code, Codex o cualquier cliente MCP podrá lanzar rastreos, leer la lista de correcciones e inspeccionar URL, en la ventana abierta, donde ves lo que hace. El servidor explica al agente cómo leer un hallazgo, qué cifras citar y cómo comprobar una corrección; cualquier corrección se convierte en una tarea de Jira con resumen, prioridad, etiquetas y pasos en el formato de Jira, y el botón Jira de cada corrección en la app hace lo mismo. Los prompts inversos dividen una página en bloques; tu agente describe cada uno y obtienes un prompt reutilizable y un ejemplo por bloque.

Search Console, en gráficos

La página Visualización de la sección Search Console: las palabras de tus consultas como treemap por clics, impresiones o número; cómo se reparten por posición, CTR e impresiones; posición frente a CTR, con las consultas a un paso de más clics; cuánto se concentran los clics; longitud de las consultas; marca frente al resto. Se dibuja en tu equipo con los datos del propio informe.

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.

Inspector de página

Elige una fila y la página se abre bajo la tabla a todo el ancho, o a la derecha: estado, indexabilidad y tema arriba, página anterior y siguiente, y después detalles con barras de longitud de title y description, cabeceras HTTP agrupadas, el snippet con los píxeles de Google, datos estructurados, la página renderizada, páginas similares y los fragmentos de la página.

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.

Rastreos programados y Google Sheets

Programa un sitio a diario, cada semana o cada mes. Los rastreos se ejecutan en tu equipo mientras la app está abierta o en la bandeja, y una ejecución que el equipo se perdió se ejecuta, se omite o se marca, como elijas. Cualquier tabla va a una hoja nueva de Google Sheets en tu Drive, con acceso solo a los archivos que crea la app.

Cambios en sitemaps

En Proyectos, añade cualquier sitio, el tuyo o el de un competidor, y la app lee sus sitemaps públicos: los encuentra por robots.txt, sigue los índices y descomprime los .gz. Cada 6 o 12 horas, cada día o cada semana mientras la app está abierta, o al pulsar Comprobar ahora, cuenta las páginas y muestra cuáles son nuevas, cuáles desaparecieron y cuáles tienen un lastmod nuevo desde la última comprobación, con las nuevas agrupadas por carpeta. Las listas se quedan en tu equipo; exportarlas requiere iniciar sesión.

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.

Barra lateral, Ctrl K y términos explicados

Siete secciones en una barra lateral, con un panel para la abierta; Ctrl B la pliega para ganar espacio y Ctrl K salta a cualquier pantalla. Las tablas caben en la ventana, con ajuste de línea o con las filas apiladas bajo los nombres de columna, así que ninguna columna queda cortada. Términos como nosnippet, X-Robots-Tag o hreflang van subrayados, con una explicación de una frase y un enlace al glosario de GetLoopLoop; se desactiva en Ajustes › General. Cada espera muestra una sola barra de progreso con el tiempo habitual en tu equipo.

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— y una comprobación de nueva versión. Ambas se desactivan en Ajustes.

GLLmolfarPreview de escritorio para Windows y Mac
Preview 0.9.23
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 · NUEVO EN 0.8.1

18 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 y qué devolver. 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.

Auditorías e informes

B1

Auditoría técnica completa → plan de acción

Primer contacto con un sitio o auditoría trimestral.

/technical-audit*

Herramientas de GLLmolfar que llama: get_statusstart_crawlwait_for_crawlget_overviewget_fixescount_pagesexplain_fixget_fix_urlssave_report

Rellenas: site, max_urls

Ver una respuesta real

Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 58 s · 35 llamadas a herramientas de GLLmolfar · sin editar, en inglés

I wrote the action plan and saved the developer report. There are no critical fixes. I didn't start a new crawl. Crawl #32 of getlooploop.com was already open: 300 URLs, mode "both", finished 2026-10-28, with embeddings and topics complete. Its GLLmolfar health score is 89/100, and the fix list has 34 fixes.

The 3 most important actions (all from crawl #32 unless marked as my judgment):

  1. cannibal (high): 14 skill pages are near-duplicates of each other, for example the Lark/Feishu mirrors and the firecrawl and googleworkspace pairs. One template change will not fix this. The URLs spread over 7 path groups, so each pair needs an editorial decision. Re-crawl to verify.
  2. hreflang.noReturn (high): 6 URLs, all /skills?category=…, which is one template. One template change fixes all 6. I suspect hreflang.missingSelf lists the same 6 pages, but that is my judgment, so check it in the same change.
  3. structured.errors (medium): 156 of 300 URLs, 52%, are missing a required JSON-LD property. I ranked it third by my judgment because of its reach. Most of the affected URLs are skill pages, which probably share one template, so one change should correct most of them. The home and product pages need their own check. I did not pull which property is missing, so run audit_url on one skill page to see it.

Other findings from the top 10:

  • ai.noAuthor (medium): 225 URLs. /glossary/* is 44% of them, so a glossary template change covers the largest part.
  • links.insecure (medium): all 14 URLs are /glossary/*.
  • a11y.unlabeled (high): 1 URL, /questions. A single-page fix.
  • ai.claims, lowContent and ai.lowMain are spread over many path groups, so they are editorial work per page.
  • images.missingAlt: I could not count it by template. The fix lists image files, and count_pages returned 0 for it.

What I did not cover:

  • Crawl limit: counts are for these 300 URLs only.
  • Samples: explain_fix and get_fix_urls returned 20 URLs each, so the lists for ai.noAuthor, structured.errors and ai.claims are samples. The template counts come from the full set.
  • Fixes not opened: fixes 11 to 34 were not opened one by one; their numbers come from get_fixes.
  • Checks not run: no Search Console data, no URL audits and no get_ai_readiness, so I make no claim about any AI bot's access.
  • Jira: nothing was sent to Jira.

Files are in the plan; the report is saved here:

  • Action plan: (work folder)\ACTION-PLAN.md
  • Developer report (HTML): C:\Users\you\Documents\gllmolfar-report-www.getlooploop.com-2026-10-28.html
B11

Backlog de Jira desde un rastreo

Pasar el trabajo técnico a los desarrolladores.

/jira-backlog*

Herramientas de GLLmolfar que llama: get_fixescreate_jira_task

Rellenas: project_key, min_share

Ver una respuesta real

Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 13 s · 3 llamadas a herramientas de GLLmolfar · sin editar, en inglés

Crawl 32 (https://www.getlooploop.com, 300 pages, health 89) is open. No crawl is running. These figures come from get_fixes for that crawl. I did not read the crawl date, so I can't give it.

Proposed Jira tasks (project SEO, up to 50 URLs each)

#Fix keySummaryPriority (GLLmolfar importance)URLs
1cannibal14 pages say almost the same as another pagehigh14 (4.7%)
2hreflang.noReturnMissing return linkhigh6 (2%)
3a11y.unlabeledForm fields without a labelhigh1 (0.3%)
4ai.noAuthorLong page without an authormedium225 (75%)
5structured.errorsRequired properties missingmedium156 (52%)
6images.missingAltMissing or empty altmedium41 (25.6%)
7ai.claimsNumbers and claims without a sourcemedium42 (14%)
8lowContent23 pages have under 250 wordsmedium23 (7.7%)
9ai.lowMainMostly menus and footers (under 40% content)medium21 (7%)

The final summaries and priorities come from create_jira_task. I will use those, not the titles above.

Excluded: the other medium fixes are each on 5% of pages or fewer. The closest are links.insecure at 4.7% (14 URLs) and external.s4xx at 4.5% (58 URLs). external.s4xx has many URLs, but its share is under the threshold. Low and insight fixes are also excluded.

Limits:

  • Tasks 4, 5, 6 and 7 cover more than 50 URLs, or close to it, so their descriptions will list only the first 50 URLs. The URL count in each task will still show the full total.
  • I have no Jira tool in this session. After you approve, I will write all tasks to JIRA-TASKS.md in the working directory.
  • I can't check for open duplicates without Jira access. If you give me the existing SEO issue summaries, I will skip any that match.

Do you approve creating these 9 tasks? You can also add or remove fixes first.

B12

Comprobación tras un despliegue

Después de un despliegue, migración o rediseño.

/release-check*

Herramientas de GLLmolfar que llama: list_crawlsstart_crawlwait_for_crawlcompare_crawlsaudit_url

Rellenas: site, key_urls

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 162 s · 9 llamadas a herramientas de GLLmolfar · sin editar, en inglés

getlooploop.com: crawl 33 vs crawl 32

Verdict: no CRITICAL items. There is one gap in my coverage. The {key_urls} placeholder in your request was never filled in, so I audited only the home page.

Top changes

  1. WARNING: more slow pages. The "URLs over 1 s" check went from 10 to 17 (+7), and the home page took 2,532 ms in the audit. The home page response was x-vercel-cache: MISS with cache-control: private, no-cache, no-store. Fixing this unblocks faster fetches by crawlers. To verify, run the crawl again and check that the slow check drops. Source: compare of crawls 32 and 33, plus the URL audit at 14:20 UTC.
  2. INFO: the 19 found and 19 lost URLs are a crawl-limit effect, not lost pages. The compare tool says newerCrawlStoppedEarly: true. It also says whyMissing is 19 "notReached", with 0 gone, 0 moved and 0 failed. Both crawls have 300 pages. The queue held 1,655 more URLs when crawl 33 stopped. To verify, run a crawl with a higher limit.
  3. INFO: the home page is not in the sitemap. The audit shows inSitemap: false. This is a judgment from one audit field. Whether it matters depends on how the sitemap is generated.

CRITICAL check

ConditionResult
Key URL not 200 or not indexableHome page is 200 and indexable. Other key URLs not checked (see Not covered).
robots.txt blocks an AI bot not blocked beforeNo. Blocked bots were [] before and [] now. robotsTxt.changed is false.
Content only after JavaScriptNo. The home page has 1,931 words raw and 1,931 rendered. Only 2 links differ.
Many fewer pages foundNo. Crawl 32 had 300 pages and crawl 33 has 300.

All changes, before and after

Source for all rows: crawl comparison, crawl 32 (2026-10-28 13:32 UTC) vs crawl 33 (14:18 UTC). Health stayed at 89 → 89. Errors stayed at 0 → 0. Non-indexable URLs stayed at 6 → 6.

WARNING (medium or higher, worse)

  • Slow URLs: 10 → 17.

WARNING (high, but better)

  • Pages that say almost the same as another page: 14 → 10.

INFO (changes in other checks)

  • Linked from one page only: 0 → 11.
  • Meta descriptions over 155 characters: 131 → 138.
  • Meta descriptions over 990 px: 65 → 72.
  • Titles the same as the H1: 1 → 6.
  • Missing or empty alt text: 41 → 42.
  • Titles over 60 characters: 137 → 138.
  • Titles over 580 px: 122 → 123.
  • H1 over 70 characters: 148 → 149.
  • Long pages without an author: 225 → 206.
  • Long pages without a date: 218 → 199.
  • 4xx external errors: 58 → 45.
  • Titles under 30 characters: 75 → 66.
  • Insecure http:// links: 14 → 12.
  • Pages that fit no topic: 1 → 0.
  • Per-URL field changes: 3 URLs gained a meaning score (null → 0.898, 0.896 and 0.899). No status, title, meta description, H1, indexability, canonical or word count changed on any URL.
  • Added URLs (19): 7 under /news/ and 12 under /notes/.
  • Removed URLs (19): all /glossary/… entries from ai-referral-traffic to anova. These are the unreached pages from the crawl limit described above.

Home page audit (2026-10-28 14:20 UTC)

  • Status and indexing: 200, indexable, canonical points to itself, meta robots index, follow, no redirects.
  • AI bots in robots.txt: each bot below is allowed by Allow: / in the * group.
  • Googlebot (Google Search and AI Overviews)
  • OAI-SearchBot (ChatGPT search)
  • GPTBot (training only)
  • ClaudeBot (training only)
  • PerplexityBot
  • Google-Extended (training only)
  • Claude-SearchBot: the audit did not report it, so I can't say whether it is allowed.
  • Schema: the audit reports one error, SoftwareApplication.aggregateRating|review. It also reports two warnings, Offer.url and ListItem.item.
  • Accessibility (axe-core): 4 serious issues and 1 moderate issue.
  • Serious: colour contrast on the "Light" toggle, the dl structure on the KPI block, dt/dd outside a dl, and a label-content mismatch on the glossary graph link.
  • Moderate: content outside landmarks.
  • Alt text: 22 of 30 images have no alt text.
  • Trust signals: trust.author is empty and dateModified is empty.

Not covered

  • Key URLs: the {key_urls} placeholder was never replaced with real URLs, so no key URL besides the home page was audited. Send the list and I'll run the audits.
  • Crawl limit: crawl 33 stopped at 300 URLs with 1,655 still queued. Pages beyond the limit were not compared, and the found/removed lists above reflect the limit only.
  • Lists: I showed the full added and removed lists, but only summarised the checks.
  • Embeddings: crawl 33 has 300 of 300 pages embedded, but I did not run topic or semantic analysis.
  • Tools that failed: two wait_for_crawl calls timed out. The crawl finished anyway, and I confirmed that with get_status.
  • Search Console: no data was used.
B13

Informe mensual para el cliente

Informes de agencia.

/monthly-report*

Herramientas de GLLmolfar que llama: list_crawlscompare_crawlsget_overviewsave_report

Rellenas: site

Ver una respuesta real

Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 28 s · 4 llamadas a herramientas de GLLmolfar · sin editar, en inglés

getlooploop.com progress report

This is not a 30-day comparison. All 12 saved crawls were run in the last 3 days, from 2026-10-26 to 2026-10-28, so no crawl from about 30 days ago exists. I compared the oldest complete crawl with the newest, and everything below covers that 2-day window only.

The client PDF is saved here: C:\Users\you\Documents\gllmolfar-report-www.getlooploop.com-2026-10-28.pdf. It was made from crawl 32, the newest one. It is a standard crawl report and does not include the comparison.

Most important points

  1. Six pages are newly not indexable. Crawl 2 (2026-10-26) had 0 and crawl 32 (2026-10-28) has 6. The comparison did not say which pages. Run get_fix_urls on crawl 32 to list them. If the six are meant to be blocked, nothing needs doing. If they are not, fixing them lets search engines index them again. A new crawl will show whether they are gone from the list.
  2. The "lost pages" figure is not real. The 109 pages listed as removed were not reached by crawl 32, which stopped at its 300-URL limit. None are confirmed gone, moved or failed. These pages are mostly /uk and /es translations, plus legal pages and older news and notes. To check them, crawl again with a higher limit.
  3. Two pages changed on getlooploop.com. The /gllmolfar meta description no longer says "up to 5,000 URLs", and its word count went from 2,445 to 3,489. The word count of /legal/privacy went from 640 to 1,265. This comes from crawl 2 and crawl 32.

Findings by source

Health score (GLLmolfar's score, not a Google score): 90 in crawl 2 (2026-10-26) and 89 in crawl 32 (2026-10-28). Errors were 0 in both.

Fixes gone and new fixes: I cannot report these. Crawl 2 was saved before version 0.7.36, so it has no per-check counts and the comparison skipped them. The work-done and new-fixes parts of your request are unanswered.

Pages found and lost (crawl 2 against crawl 32):

  • Found: 259, mostly /glossary/ pages and /skills/ pages, plus one news article.
  • Not reached: 109, as explained above.
  • Not comparable: the crawls used different limits, 150 pages and 300 pages.

AI bots in robots.txt: robots.txt did not change between the two crawls. No AI bots are blocked in either one. I did not run the bot check, so I have not tested what each bot can actually fetch. The comparison does not tell me what robots.txt says about any single bot, so I make no claim for OAI-SearchBot, Claude-SearchBot or Googlebot.

Search Console: I have no Search Console tool in this session, so there is no comparison of clicks, impressions or CTR and no list of queries that fell by more than 20%.

Not covered

  • Crawl 32 hit its 300-URL limit, so it is a sample of the site.
  • The comparison has no per-check data, so there is no fix comparison.
  • No Search Console data.
  • I did not run the AI bot probe.
  • Embeddings exist for crawl 32 (300 pages). I did not use them for topics or duplicate pages.

One-page summary for the client

Where the site stands: The website is in good shape. Our health score is 89 out of 100, and the crawler found no broken pages. This is a first check, so we have no earlier month to compare with yet.

What changed this week: Two pages were updated: the GLLmolfar product page and the privacy policy. No search or AI crawlers are blocked on the site.

One thing to look at: Six pages are now marked "not indexable", which means search engines will skip them. Some pages are meant to be hidden, so we will check whether these six are. Fixing any that should not be hidden lets search engines include them. We cannot promise this will raise rankings or traffic.

Priorities for next month:

  1. Check the six pages. Decide whether they should be indexed, fix any that should, and run the crawl again to confirm.
  2. Run a full crawl. Raise the page limit so every page is covered, including the Ukrainian and Spanish pages the last crawl did not reach. That gives a reliable baseline for next month's comparison.
  3. Connect Search Console. Without it we cannot show clicks, impressions and falling search queries. With it, the next report can show real search results.

Should I run the full crawl now? I can also list the six non-indexable pages from crawl 32.

B15

Corregir en el código y verificar

El agente trabaja en el repositorio del sitio.

/fix-and-verify*

Herramientas de GLLmolfar que llama: audit_urlstart_crawlwait_for_crawlcompare_crawls

Rellenas: urls

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

Búsqueda con IA

B2

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

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

/ai-readiness*

Herramientas de GLLmolfar que llama: get_statusget_ai_readinessget_fixesget_fix_urlscount_pagesaudit_urlexplain_fix

Rellenas: site, max_urls, template_urls

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 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.
B3

Preparación de una página para agentes

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

/page-agent-readiness*

Herramientas de GLLmolfar que llama: audit_urlsemantic_search

Rellenas: url

Ver una respuesta real

Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 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.
B4

Citabilidad y plan de reescritura de una página

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

/citability*

Herramientas de GLLmolfar que llama: semantic_searchaudit_urlget_pagesmeasure_text

Rellenas: url, questions

Ver una respuesta real

Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 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.
B5

Prueba de cobertura de preguntas (fan-out)

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

/question-coverage*

Herramientas de GLLmolfar que llama: semantic_search

Rellenas: topic, audience

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 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.

B8

Borrador de llms.txt

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

/llms-txt*

Herramientas de GLLmolfar que llama: get_overviewget_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 · 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.

Contenido

B9

Brief de actualización de una página

Una página que pierde clics, está desfasada o la supera un competidor.

/refresh-brief*

Herramientas de GLLmolfar que llama: audit_urlget_pagessemantic_searchget_fix_urlsmeasure_text

Rellenas: url

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 86 s · 14 llamadas a herramientas de GLLmolfar · sin editar, en inglés

Refresh brief: https://www.getlooploop.com/glossary/ai-visibility

Sources. Crawl 32 of getlooploop.com (28 Oct 2026, 300 of 300 pages, embeddings on) gave the fix list, get_pages data and semantic search. A live URL audit on 28 Oct 2026 at 14:11 GMT gave status, text, headings, JSON-LD and robots.txt. measure_text on the current page text gave passage positions. Anything marked "judgment" is mine.

The 3 most important changes

  1. Add an author and real dates.
  2. Crawl 32: ai.noAuthor and ai.noDate both fail for this page, and get_pages returns empty author, datePublished and dateModified.
  3. URL audit: the visible text says "Updated September 2026" and "Prepared at GetLoopLoop", with no named person. The DefinedTerm JSON-LD has no dates and no author.
  4. Change: show a byline linked to an author page, with a Person that has sameAs. Add datePublished and dateModified to the JSON-LD and show the same dates on the page.
  5. What it unblocks: an assistant can see who stands behind the page and how current it is.
  6. Verify: run audit_url and check that trust.author, trust.datePublished and trust.dateModified are filled. Then re-run crawl 32's checks and confirm the URL no longer appears under ai.noAuthor and ai.noDate.
  1. Move the SEO-difference answer up, and add sections for the questions this page answers worst.
  2. measure_text, current page, 10 passages: the answer to "How is AI visibility different from SEO?" sits at passage 8, although the tool's rule is that the answer should appear by passage 2. Its score is 0.727, so the content is fine and only the position is wrong.
  3. measure_text, current page: the robots.txt question scores 0.464 at passage 6, and the timing question scores 0.470 at passage 3. Both scores are weak.
  4. Semantic search, crawl 32, rank of this page among our pages: see the table in the next part.
  5. Change: add the sections listed in "Sections to add" below.
  6. Verify: run measure_text again with the new draft and the same six queries, and look for scores above the current ones and the SEO answer at passage 2 or earlier.
  1. Source or remove the unsourced numbers, and label the example.
  2. URL audit: the only source is the generic "Google Search Central" link. The page says "at least three high-quality backlinks" and "a few weeks" with no source.
  3. URL audit: the "Worked example" is a made-up BrandX quote written as if it were a real test.
  4. Change: link each figure to its source, or reword it as a judgment. Mark the BrandX example as illustrative.
  5. Verify: audit_url should show trust.statSentences and external content links that match the claims.

Facts and dates to update

  • Visible date. "Updated September 2026". Today is 28 Oct 2026. Update it only after you actually change the content, and put the same date in dateModified.
  • Crawl 32 fix list for this page: titles.below30, ai.noAuthor, ai.noDate, content.lowRatio, headers.insecureCookies, security.no_xcto, security.no_csp, security.no_xfo, security.no_referrer.
  • Title. The title is "AI Visibility — GetLoopLoop", 27 characters. Add the topic.
  • Section 03 (measurement). It names "Google's AI Search or Microsoft Copilot". Check the product names against current ones.
  • Section 03 (measurement). It says "no public score" and does not mention our own tools, Brandscope or Vectorscope. Judgment: say what they measure.
  • Section 08 answers. Some start with "Yes" or "No" and do not answer the question asked. For example, "why isn't my brand showing up?" is answered with "Yes, the AI may not be pulling…".
  • AI access, URL audit of 28 Oct 2026. robots.txt allows Googlebot, GPTBot, OAI-SearchBot, ClaudeBot, PerplexityBot and Google-Extended for /glossary (group *, line 17). Bot by bot:
  • OAI-SearchBot: allowed, so ChatGPT search can fetch the page.
  • Googlebot: allowed, so Google Search and AI Overviews can fetch it.
  • ClaudeBot: allowed. It controls training only, and says nothing about Claude search.
  • Claude-SearchBot: not checked, because the tool did not list it.
  • Sitemap. The URL audit reports inSitemap: false. Check sitemap.xml yourself before acting.
  • Alt text. The URL audit reports 6 images with no alt text. Crawl 32 does not list images.missingAlt for this page, so the two sources disagree. Check this.
  • Accessibility, axe-core in the URL audit: two serious violations, color-contrast (3 nodes) and link-in-text-block (the CC BY 4.0 link).

Sections to add

Rank is this page's rank among our pages in semantic search on crawl 32. "Passage" is the best-matching passage number from measure_text on the current page.

QuestionRankScorePassageBest on-site page
What is AI visibility?10.6151this page
How is AI visibility different from SEO?10.5998this page
How do I measure my brand's AI visibility?20.6284/brandscope (0.668)
How do I get my brand cited by ChatGPT and other AI assistants?30.5282/brandscope (0.588)
Which AI crawlers should I allow in robots.txt to appear in AI search?130.4206/glossary/robots-txt (0.550)
How long does it take for changes to show up in AI answers?40.4173/questions (0.486)

What to add:

  • A robots.txt section by bot. Say that OAI-SearchBot controls ChatGPT search, that Claude-SearchBot controls Claude search, and that Googlebot controls Google Search and AI Overviews. Say that GPTBot, ClaudeBot and Google-Extended control training only. This is the weakest question (rank 13).
  • A short section on timing. The current answer, "a few weeks", has no source. Describe what to re-check and when. Do not promise a timeline.
  • A "how to measure" section that names the tools. It should say what Brandscope and Vectorscope show, and link to them. /brandscope currently beats this page on this question.
  • A "how to get cited" section. Cover which passages assistants quote. Judgment: link /news/brands-in-ai-answers-october-2026-a-market-analysis, which scored 0.548 on this question.

Limit of these results. Semantic search returned only the page-level block, headed "GetLoopLoop", for every result, so it could not name which section answers. I used measure_text passage numbers instead. Only passages 1 (intro), 3 (section 02) and 4 (section 03) have previews. The other numbers are positions only.

Sections to merge or remove (judgment, plus one measured fact)

  • Section 08 "Asked out loud" and section 07 FAQ. Both are Q&A blocks that repeat each other, and the FAQ JSON-LD copies all 9 of them. Merge them into one FAQ of roughly 5 questions. Drop the generic ones, "Should we invest now or wait?" and "Is it still relevant after LLM updates?", unless you add specifics.
  • Section 05 and the SEO FAQ answer. Both say AI visibility is different from SEO. Keep the answer once, near the top.
  • "Quick audit checklist" and section 02. Both list the same actions. Keep one.
  • The last sentence of section 01. "It is how often a brand appears…" repeats the definition in the intro.
  • Section 09. It is an alphabetical list of unrelated terms: "Accountability, Action Space, ads.txt…". Replace it with 4 to 5 terms that really relate to this one.
  • Cannibalization. The nearest page is /glossary/ai-overview at cosine 0.766, below the 0.94 cannibalization threshold. This page is not in the crawl 32 cannibal list. No merge is needed.

Internal links to add

  • From the crawl 32 "links" opportunities: I searched all 239 for addLinkOn or linkTo pointing at this URL. There are none that point to it.
  • The only entry involving this page goes outward: add a link from this page to /glossary/ai-overview with the anchor "ai overview" (similarity 0.814).
  • Check. The single-page audit shows inlinks: 0 and linkScore: 0 for this page. That figure comes from the audit, not from the full crawl, so confirm it in crawl 32 before saying nothing links here.
  • Judgment, not from the tool: /brandscope, /glossary/robots-txt, /glossary/share-of-voice and /glossary/ai-referral-traffic are the closest pages by meaning. Link them from the new sections above.

How to verify after publication

  1. Run audit_url on the page. Check author, dates, title length, JSON-LD and the 6 robots.txt verdicts, and add a check for Claude-SearchBot if the tool supports it.
  2. Run measure_text with the final draft and the same six queries. Look for the SEO answer at passage 2 or earlier and higher scores on the robots.txt and timing questions. Confirm that the nearest page stays below 0.94.
  3. Run a new crawl, or audit_url for this page, and confirm the URL is no longer listed under ai.noAuthor, ai.noDate and titles.below30.
  4. Run the semantic searches again and compare ranks with the table above.
  5. Check the Spanish version /es/glossary/ai-visibility. It is linked through hreflang and needs the same date and author changes.

What I did not cover

  • Search Console. There is no Search Console tool in this session, so I have no 90-day queries and no comparison with the previous 90 days.
  • Crawl 32 size. It reached its limit of 300 URLs with 0 queued, so it may not include every page on the site.
  • Semantic search. It gave page-level results only, with no named sections.
  • measure_text baseline. I passed the page text as plain text, so the tool counted 3 passages. The live page measured 10, and I used the live page numbers.
  • Not checked. I did not check Claude-SearchBot in robots.txt, and I did not check llms.txt.
  • Other fixes. The security-header and cookie fixes are low importance and not covered here.

I can publish this as a shareable page if you want to pass it to the content team.

B10

Revisión de contenido desfasado, sin fecha y sin fuentes

Higiene E-E-A-T trimestral.

/stale-content*

Herramientas de GLLmolfar que llama: get_overviewget_pagescount_pagesaudit_url

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 113 s · 22 llamadas a herramientas de GLLmolfar · sin editar, en inglés

Stale, undated and unsourced content: crawl 32

Sources:

  • Crawl 32 is the open crawl of getlooploop.com, 28 Oct 2026. It holds 300 pages, all with embeddings, and the URL limit was not hit.
  • URL audit means audit_url runs on 10 pages, 28 Oct 2026 at about 14:13 UTC.
  • No Search Console data was used.

No crawl was running. I did not start one.

Most important changes

  1. Add a visible byline linked to an author profile page, plus a JSON-LD author Person. (crawl 32) 225 of 300 pages fail ai.noAuthor. I audited 10 of them (URL audit). The only Person in their JSON-LD is the site founder, "Olexandr", inside the sitewide Organization block. The skill pages name the publisher repo, such as agricidaniel/claude-seo, as an Organization author. The /questions answers are the exception. They carry a Person author with a LinkedIn URL, not an on-site profile.
  2. The pages are built from templates, so this is a handful of template edits.
  3. I did not check whether /about#author (the founder's @id) resolves to a real page. Check that first.
  4. To verify, re-run the crawl, or run audit_url on one page, and confirm ai.noAuthor no longer lists the URL.
  5. Show a publish or modified date on the page, and put the same date in JSON-LD. (crawl 32) 218 of 300 pages fail ai.noDate.
  6. Every page that fails ai.noDate also fails ai.noAuthor.
  7. On the 10 audited pages, JSON-LD has dateModified on only 2: /ai-volatility (2026-10-28) and /gllmolfar (2026-10-27). /questions has per-question dateCreated in JSON-LD (Aug 2026), but I did not see a visible date for it in the text I read.
  8. On the skill pages the only visible date is "Last read Oct 26, 2026". That is a directory sync date. It is not a publish or modified date, and JSON-LD has none.
  9. Verify with ai.noDate.
  10. Link a source next to each number. (crawl 32) 42 pages fail ai.claims. 36 of them are in Technical seo (24) and Workflows published (14), and these are mostly skill pages.
  11. On the 10 audited pages (URL audit), extContentLinks is 0 on every page, so there are no outbound links inside the content.
  12. On /ai-volatility the figures are the site's own measurement, and a "How do we measure any of this?" section exists. Link that method from the numbers themselves.
  13. Verify with ai.claims.

ai.stale flags 0 pages in crawl 32. That does not show the content is fresh. With 218 pages undated, the checker cannot judge age for them.

Access is not the problem. (URL audit) robots.txt allows Googlebot, OAI-SearchBot and ClaudeBot on all 10 pages. These fixes are on-page.

Pages by topic (crawl 32)

Each page was scored by how many of the 4 fix keys it fails. ai.stale is 0 for every page, so the maximum score is 3. 37 pages score 3.

TopicPagesnoDatenoAuthorclaimsScore 3Score 2Score 1Score 0
Workflows published1015252141240247
Technical seo55444424222229
Ai getlooploop535353005300
Ad affiliate333232003201
Ai news301420321279
Vectorscope ai127811614
Text robots101010001000
Testing variance55500500
No topic11100100

The score columns come from my own set arithmetic over the get_pages lists. They sum to each topic's total.

The topic labels are GLLmolfar's embedding clusters, and they are loose. "Ai news" holds glossary hubs and category pages, not only news. I did not check each cluster.

URL audit of 10 pages

All 10 fail all three of ai.noDate, ai.noAuthor and ai.claims. Another 27 pages tie at the same score, so this is a spread across topics that I chose, not a ranking.

Page (topic)Visible dateJSON-LD date agreesAuthor with profileSource for a number
/ai-volatility (Ai news)"Today · Oct 28" reading label, not a publish datedateModified 2026-10-28 on Dataset, no datePublished. Same day as the label.Missing. Founder only, in sitewide JSON-LD.Own measurement, method section present, 0 external links
/gllmolfar (Technical seo)None in the text I readdateModified 2026-10-27, nothing visible to agree withMissingProduct limits (50,000 / 5,000 URLs) with no source
/questions (Ai news)None seen in the text I readPer-question dateCreated (Aug 2026)Person in answer JSON-LD, LinkedIn URL, no on-site profile12 statistic-like sentences, 0 external links
/voicescope (Vectorscope ai)None in the text I readNo datesMissing12 statistic-like sentences, 0 external links
/skills/agricidaniel/claude-seo/seo"Last read Oct 26, 2026" (sync date)No datesOrganization (repo name) onlyInstall count 9,087, labelled "from the directory"; 0 in-content links
/skills/coreyhaines31/marketingskills/seo-auditSame sync dateNo datesOrganization only238,125 installs, same pattern
/skills/coreyhaines31/marketingskills/content-strategySame sync dateNo datesOrganization only164,414 installs, same pattern
/skills/wshobson/agents/rag-implementationSame sync dateNo datesOrganization only14,011 installs, same pattern
/skills/google/skills/bigquery-ai-mlSame sync dateNo datesOrganization only7,144 installs, same pattern
/skills/yuan1z0825/nature-skills/nature-citationSame sync dateNo datesOrganization only15,696 installs, same pattern

The skill pages already show an install count labelled "from the directory", with a skills.sh link in the text and in the schema. The gap is that this is not a source link attached to the number inside the content. I did not read the pages in full, so the dates and sources marked "none in the text I read" could appear lower on the page.

Plan per topic

  • Workflows published (101 pages) and Technical seo (55 pages). These are mostly skill pages from one template.
  • Add a "Last reviewed" or modified date to the template, and fill dateModified in JSON-LD from the same value. Use the directory sync date only if it is labelled as that.
  • Add a GetLoopLoop reviewer byline linked to a profile page. Keep the skill's publisher in the page as the skill's publisher, not as the page's author.
  • Attach the source link to the install counts and the "+x%" figures. Fix the 36 ai.claims pages first.
  • Verify with a re-crawl and ai.noDate, ai.noAuthor and ai.claims.
  • Ai getlooploop (53) and Ad affiliate (33). All 85 are glossary entries that fail the date and author checks, and none fails ai.claims.
  • Add datePublished and dateModified to the glossary template.
  • Add an author or reviewer line.
  • Fix the template once. One template change covers the whole topic.
  • Verify with a re-crawl, then ai.noDate and ai.noAuthor.
  • Ai news (30). This is the only topic where ai.noAuthor (20) exceeds ai.noDate (14). The news articles and /news have a date but no author.
  • Add a byline to the 5 news articles and /news.
  • Add the date and byline to /ai-volatility, /questions and the three language glossary hubs.
  • Link the method next to the volatility figures.
  • Verify with ai.noAuthor, ai.noDate and ai.claims.
  • Vectorscope ai (12). Add a date and author to /voicescope, /brandscope, /patternscope, /reviewscope, /vectorscope and /methodology. Add a byline to /vectorscope/claude-skill, which already has a date. Source the numbers on /voicescope. Verify with ai.noDate and ai.noAuthor.
  • Text robots (10), Testing variance (5), No topic (1). These are glossary entries. The template fix for the glossary covers them. /glossary/robots-txt and /glossary/llms-txt are the pages where a date matters most, because the topic changes over time. Verify with ai.noDate and ai.noAuthor.

What I did not cover

  • Only 10 of the 37 pages that score 3 were audited. The other 27 are in the ai.claims list. I did not audit any score 2 page or any page from the topics with no claims.
  • audit_url returned only the start of each page's text, so whether a visible date or byline appears further down is unconfirmed.
  • I did not check whether /about exists or has a Person profile.
  • My first ai.noDate and ai.noAuthor calls were too large to print. I re-fetched them with only the columns url and topic, and all 218 and 225 rows came back. The set arithmetic for the table is mine.
  • The shell was unavailable, so I did no scripted analysis of the saved files.
  • The audits also showed schema errors (for example SoftwareApplication.aggregateRating|review) and security-header fixes. I did not report those here.
  • No Jira tasks were created and no Search Console data was used.

I can write the Jira tasks (one per fix key) or publish this as a shareable page if you want either.

B14

Plan de datos estructurados

Errores de schema o falta de schema en plantillas clave.

/structured-data*

Herramientas de GLLmolfar que llama: count_pagesget_pagesaudit_urlexplain_fix

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 97 s · 12 llamadas a herramientas de GLLmolfar · sin editar, en inglés

Structured data plan for getlooploop.com

Source: crawl 32, 2026-10-28 (300 pages, health 89). The page-level findings come from URL audits run on 2026-10-28 at about 14:15 UTC. Fix counts come from count_pages. The proposed JSON-LD is my judgment.

Crawl state: no crawl was running. I did not start one.

The 3 most important changes

  1. *Fix the SoftwareApplication block on the /skills/ template.** This one template has 147 of the 156 error pages and 147 of the 161 warning pages.
  2. The error is aggregateRating|review missing.
  3. The warnings are Offer.url, Offer.availability, and Organization.url/logo/sameAs.
  4. The Organization warnings probably come from the inline author, which has only a name.
  5. Don't invent ratings. The pages show install counts, not reviews. Add the missing Offer and author properties and decide separately about the rating error (see Section 3).
  6. Make the news headline match the visible H1 and clean up dateModified.
  7. The headline in the JSON-LD is "Search & AI news, 22–26 Oct 2026: AI Overviews pass 80%". The visible H1 is "AI Overviews pass 80% as the clicks stay thin".
  8. dateModified is 2 ms after datePublished, so it looks auto-generated. The page shows no modified date.
  9. Fix /gllmolfar.
  10. It lacks offers, which is an error.
  11. It also lacks a rating or review.
  12. Its publisher is an inline Organization that lacks logo and sameAs. Point it at the #organization node with an @id reference.
  13. The page says "Preview 0.7.35", but get_status reports the local app as GLLmolfar 0.8.1. Confirm which version is current before you publish softwareVersion.

1. Counts by template (crawl 32)

Fix keyPagesWhere
structured.invalid0none
structured.missing0none
structured.errors156147 /skills/* pages. The other 9 are /, /gllmolfar, /brandscope, /methodology, /patternscope, /reviewscope, /voicescope, /vectorscope and /vectorscope/claude-skill.
structured.warnings161The same 147 /skills/ pages, plus the same 9 non-skill pages, plus /free-tools, /news, /notes and 2 /news/ pages.

Every page has some JSON-LD. The problem is incomplete properties, not absent markup.

2. URL audits (one URL per template)

TemplateURL auditedTypes foundErrorsWarnings
Home/Organization, WebSite, SoftwareApplication, WebPage, FAQPage, ItemList`SoftwareApplication.aggregateRating\review`Offer.url, ListItem.item
Product/gllmolfarOrganization, WebSite, SoftwareApplicationSoftwareApplication.offers, `aggregateRating\review`Organization.logo, Organization.sameAs
Skill/skills/agricidaniel/claude-seo/seo-schemaOrganization, WebSite, SoftwareApplication, WebPage`aggregateRating\review`Organization.url/logo/sameAs, Offer.availability, Offer.url
News post/news/ai-overviews-pass-80-as-the-clicks-stay-thinOrganization, WebSite, NewsArticle, BreadcrumbList, FAQPagenoneNewsArticle.image

3. Proposed JSON-LD

Facts in the snippets come from the audited pages. Anything marked TODO needs a real value from you.

Home (/)

The Organization already exists, and its sameAs lists only X and Discord. Add real profiles you own, such as a company LinkedIn page or GitHub org. Don't add a profile that doesn't exist.

{
  "@context": "https://schema.org",
  "@graph": [
    {
      "@type": "Organization",
      "@id": "https://www.getlooploop.com/#organization",
      "name": "GetLoopLoop",
      "url": "https://www.getlooploop.com",
      "logo": "https://www.getlooploop.com/brand/getlooploop-logo.jpg",
      "sameAs": [
        "https://x.com/Looploopnow",
        "https://discord.gg/Z6cRuhprMa"
        /* TODO: add company LinkedIn / GitHub URLs if they exist */
      ],
      "founder": { "@id": "https://www.getlooploop.com/about#author" }
    }
  ]
}

In the existing home SoftwareApplication, add "url" to the Offer. Use the page that explains invite-only access, which is a TODO. In the ItemList, give each ListItem an item as well as url:

{ "@type": "ListItem", "position": 1, "name": "Vectorscope",
  "item": "https://www.getlooploop.com/vectorscope" }
  • I only saw the first part of the home JSON-LD. The tool output cut it off partway through the ItemList. Re-check the rest after the change.
  • The home Offer says price 0 with LimitedAvailability. The visible text says "Invite-only". Make sure the markup says the same.
  • Don't add a date to the home page. The only date I saw on it belongs to an article card.

Posts (/news/*)

There are no errors. Change the headline, drop or correct dateModified, and add an image:

{
  "@context": "https://schema.org",
  "@type": "NewsArticle",
  "@id": "https://www.getlooploop.com/news/ai-overviews-pass-80-as-the-clicks-stay-thin#article",
  "headline": "AI Overviews pass 80% as the clicks stay thin",
  "datePublished": "2026-10-26T18:18:47.010Z",
  "dateModified": "2026-10-26T18:18:47.010Z",
  "image": ["TODO: https://www.getlooploop.com/<real article image>"],
  "author": {
    "@type": "Person",
    "@id": "https://www.getlooploop.com/about#author",
    "name": "Olexandr",
    "url": "https://www.linkedin.com/in/olexandr-tsyrkin-07460539"
  },
  "publisher": { "@id": "https://www.getlooploop.com/#organization" },
  "mainEntityOfPage": "https://www.getlooploop.com/news/ai-overviews-pass-80-as-the-clicks-stay-thin"
}
  • Headline: the new text matches the visible H1.
  • Dates: datePublished matches the visible "26 October 2026". Only set dateModified to a later time if the page shows a real update.
  • Word count: the current wordCount of 2847 differs from the crawler's count of 3161 words. I left it out. Add it back only if it is computed from the rendered text.
  • Author: "Olexandr" matches the visible author line.

Product (/gllmolfar)

Use SoftwareApplication. Product doesn't apply to a desktop app.

{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "@id": "https://www.getlooploop.com/gllmolfar#software",
  "name": "GLLmolfar",
  "url": "https://www.getlooploop.com/gllmolfar",
  "applicationCategory": "SEO software",
  "operatingSystem": "Windows 10 or later, macOS on Apple silicon",
  "softwareVersion": "TODO: confirm (page says 0.7.35, local app is 0.8.1)",
  "offers": {
    "@type": "Offer",
    "price": "0",
    "priceCurrency": "USD",
    "url": "https://www.getlooploop.com/gllmolfar",
    "availability": "https://schema.org/InStock"
  },
  "publisher": { "@id": "https://www.getlooploop.com/#organization" }
}
  • Offer: the page's visible text says "50,000 URLs per crawl, free with an account". price: 0 agrees with that. If paid levels get their own offers, add them.
  • dateModified: the existing markup says 2026-10-27. I found no visible date to match it, so drop it unless the page shows one.

Skills (/skills/*)

Keep the existing SoftwareApplication, WebPage and BreadcrumbList. Change the author and the Offer:

"author": { "@type": "Organization", "name": "agricidaniel/claude-seo",
            "url": "TODO: the publisher's real URL shown on the page" },
"offers": { "@type": "Offer", "price": "0", "priceCurrency": "USD",
            "availability": "https://schema.org/InStock",
            "url": "https://www.getlooploop.com/skills/agricidaniel/claude-seo/seo-schema" }
  • Generate these fields from the template data, so every skill page gets its own publisher and URL.
  • The name seo-schema and the 7,079 installs agree with the visible page.
  • Rating or review error: you have two choices.
  • Add a real aggregate rating or review only if you collect and show them.
  • Otherwise accept the error as "not applicable". I can't tell from the crawl whether the rating-or-review property is required for rich results, so check the current Google documentation.

4. Google changes the rich result types

Google changes the rich result types. Check the current Google documentation before you depend on one. The seo-schema skill page on your own site, a data point from the crawl, says Google retired several types in 2025. FAQPage is one that its text flags as having no Google SERP rich result benefit.

5. Verify

  • Run audit_url on each representative page after the change. The page is clean when its structured.errors and structured.warnings keys no longer list it.
  • Run a new crawl to confirm the full templates.
  • Check the markup against Google's current documentation or Rich Results Test. This change only unblocks eligibility and does not promise a rich result.

6. What I did not cover

  • Crawl limit: crawl 32 hit its limit of 300 pages. A larger skills directory or other sections may exist.
  • Pages I audited: only 4 pages, one per template. I did not audit /methodology, /brandscope, /patternscope, /reviewscope, /voicescope, /vectorscope, /free-tools, /news and /notes. They may differ from my samples.
  • Home JSON-LD: truncated in the audit output, as noted above.
  • Lists: I saw all 156 error URLs and all 161 warning URLs. I cut none.
  • Tools and sources: no tool failed. I did not use Search Console or the Rich Results Test. Embeddings were not relevant to this task.

Appendix: pages per template with warnings or errors

The full URL lists are in get_fix_urls for structured.errors (156) and structured.warnings (161). The /skills/* group has about 60 publisher folders. The largest are claude-seo (25 pages), affaan-m/ecc (11), google/skills (10), marketingskills (9), aaron-he-zhu/seo-geo-claude-skills (8) and wshobson/agents (8).

B18

Prompts para un tipo de página (prompts inversos)

Briefing para redactores o un modelo, para crear más páginas como la mejor.

/reverse-prompts*

Herramientas de GLLmolfar que llama: reverse_prompts_readreverse_prompts_buildreverse_prompts_get

Rellenas: url, page_type

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Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 114 s · 4 llamadas a herramientas de GLLmolfar · sin editar, en inglés

Brief for a product landing page (reverse prompting)

Source: reverse prompting of https://www.getlooploop.com/gllmolfar, run mvs7769j56e7de7a, 2026-10-28. Build status: built, 13 blocks from 15 candidates. This is my reading of the page (judgment), not crawl or audit data.

get_status showed no crawl running (crawl 32 loaded, idle). I did not start one.

Three things to know first

  1. The page opens with the result, then admits it is a preview. Hero first, then a block saying the build is unfinished and unsigned. Keep that order: candour comes early, before the feature detail.
  2. Every claim comes with a limit. Scores, similarity and AI-readiness are described as leads for human review, never as rank or traffic promises. Copy this pattern in each feature block.
  3. The build passed on the second try. The first build listed 6 overlap problems (lines repeating 6+ words from the page). I fixed only those lines and rebuilt.

Page profile

  • Language: en
  • Fictional example product: Sitelens, a desktop auditor that scans a site, shows how assistants read it, and ranks repairs.
  • Page type: product landing page for a downloadable, preview-stage desktop tool.
  • Audience: SEO specialists, content teams, freelance consultants and site owners who must decide what to repair first.
  • Awareness: comparing_solutions.
  • Tone: candid, precise, technical but plain; formality 3; second person.
  • Promise: {product} gives {audience} a clear, evidence-backed list of what to repair next, without guessing, spreadsheet juggling or sending page text to a cloud service.
  • Logic: result and download, then preview limits, views, method, evidence, data boundary, answers, honest rival table, closing download.
  • Threads:
  • each finding links to the exact pages behind it;
  • analysis runs on the user's machine;
  • limits are stated openly;
  • a score is a lead for review.

Block prompts

Each prompt starts "Write a … block for {product}, aimed at {audience}. Write in English." Below are the job and the structure, with word counts as the build gives them.

#BlockTypeJobStructure (words)
1HeroheroSay what the tool does and offer a download for both systems, with the limits stated.Headline 8–12 (three short imperatives, no product name); intro 30–40; two download buttons 5–9 and 8–11; terms notice 6–10; limits note 28–40
2Preview disclosureotherSet the expectation that this is a preview.Headline 5–8; statement 18–26; 4 caveats of 8–24; reassurance 6–10; changelog link 4–7
3Unsigned build guideotherGet the visitor past the security warning.Headline 7–11; explanation 30–40; 3 options (h3 3–5, p 15–35); command hints 8–12
4Audience stripotherName the roles in one line.Lead-in 3–5; 4 role chips of 1–3
5View galleryfeaturesOne scan opens into many views, with the AI-access view highlighted.Headline 5–9; intro 22–28; 4 groups (label 2–4, 5 view names); question 8–11; answer 34–42
6Scan walkthroughhow_it_worksMake each crawler step and the entry modes visible.Headline 6–9; intro 24–30; 4 steps (h3 3–6, p 20–45); modes headline 5–7; 4 modes (h4 2–3, p 14–26)
7Signal cataloguefeaturesList the signal families and the crawler's conduct rules.Headline 4–7; intro 22–26; 4 families (h3 2–4, p 18–25); conduct note 80–95
8Capability cataloguefeaturesMap the whole workspace from findings to decisions to automation.Headline 5–9; intro 22–28; 15 cards (h3 1–5, p 25–110)
9Local analysis explainerotherShow that meaning analysis runs locally and how to read it.Headline 5–8; method 28–34; depth modes 75–90; 3 similarity cues; disclaimer 10–14
10Data boundaryotherMake clear what stays local and what is sent.Headline 5–8; local storage 30–40; no cloud AI 18–24; telemetry 40–50; 5 data-flow rows
11QuestionsfaqAnswer scope, method, limits and updates.Headline 3–5; intro 6–10; 10 Q&As (question 4–11, answer 35–135)
12Honest comparisoncomparisonCompare with two unnamed rivals and concede where they do more.Headline 3–5; intro 18–22; legend 5–7; 20 rows (name 2–9, cells 20–60); source note 25–30; footnotes 20–25
13Final downloadctaRepeat the download offer and the consent and link-validity notes.Headline 5–7; offer 15–19; two buttons; terms notice 6–10; link note 6–9

Techniques that recur across blocks

  • Put the result before the mechanism, and the mechanism before the numbers.
  • Open each answer or card with the direct point, then one concrete detail, then a limit.
  • Give each caveat its own plain sentence.
  • Mark every comparison row with a symbol and a short qualifier, and concede rows where rivals do more.
  • Avoid: superlatives, ranking or citation promises, naming rivals, apologetic wording.

What I did not cover

  • Dropped candidates: b01 (navigation, tool menu and footer links) and b12 (two placeholder release notes). The brief also excluded one 13-word overlay.
  • Truncated source text: several long paragraphs in the brief end in "…". My word ranges for those blocks rest on the brief's counts, not the full text.
  • Build warnings: the build flagged 7 example lines as outside the stated range by more than 20%. The blocks are fine, and these are example texts only:
  • Signal family 1 paragraph: 14 words against 18–25.
  • Conduct note: 51 words against 80–95.
  • Depth modes paragraph: 45 words against 75–90.
  • Local storage paragraph: 30 words against 40–50.
  • FAQ answer 1: 23 words against 35–135. It is only just outside the 20% tolerance and sits under the lower bound.
  • Comparison headline: 7 words against 3–5.
  • Comparison row 1 cell: 7 words against 20–60.
  • Fix: lengthen or shorten those example lines, or widen the ranges, then rebuild.
  • Names removed: the brand, rival and tool names are replaced with generic wording, as the rules require, so the examples contain no real product names.
  • Not run: no crawl, semantic search, URL audit or Search Console data. Nothing here is a ranking or traffic claim.

To verify the changes, rebuild with the corrected example lines and check that reverse_prompts_build returns no warnings.

B16

Comparación de pasajes con un competidor

«¿Por qué los citan a ellos y no a nosotros?»

/competitor-passages*

Herramientas de GLLmolfar que llama: list_crawlsopen_crawlsemantic_searchstart_crawlwait_for_crawlaudit_url

Rellenas: competitor, questions

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

Enlaces y canibalización

B6

Limpieza de canibalización

Aparece la comprobación de canibalización o dos páginas se reparten una consulta.

/cannibalization*

Herramientas de GLLmolfar que llama: get_fixesget_fix_urlsget_pagesaudit_urlsemantic_search

Ver una respuesta real

Claude Code (Sonnet) sobre un rastreo de getlooploop.com, 300 páginas, 28 de octubre de 2026 · 40 s · 12 llamadas a herramientas de GLLmolfar · sin editar, en inglés

Cannibalization report: crawl 32 (getlooploop.com)

Source: crawl 32, 300 URLs crawled, 300 with embeddings. The crawl is loaded and idle, so I started no new crawl. The date and any URL limit were not in get_status. The account limit is 1,000,000 URLs, so it did not cut anything. I did not use Search Console.

The 3 changes that matter most

  1. Fix the title and H1 template on /skills/ pages (crawl 32 + my judgment).
  2. Every page reads "X — {Topic}, an agent skill published by {publisher}", and the first section of each page repeats the same sentence.
  3. That template is why these 14 pages score 0.74–0.82 against each other.
  4. The pages differ only in skill name and publisher. Adding a line that says what each skill does, and how it differs from its neighbours, is the single change that helps every pair below.
  5. To verify, re-crawl and check that cannibal no longer lists these URLs.
  6. Same skill, three publishers: the Lark meeting-summary and standup-report pages (6 URLs).
  7. Each skill has three listings: larksuite/cli, open.larksuite.com and open.feishu.cn. The nearest-page scores are 0.78 and 0.74 (meeting-summary) and 0.79 and 0.76 (standup-report).
  8. Same intent. Pick one canonical listing per skill after a person checks whether the three have the same source. Install counts from the crawl are 809,000 for open.feishu.cn, 466,168 for larksuite/cli and 6,936 for open.larksuite.com.
  9. A canonical on the small open.larksuite.com listing removes it from the index. It unblocks the other two from competing with it. It does not guarantee any ranking.
  10. Same skill, two repos: firecrawl-crawl.
  11. firecrawl/cli has 80,778 installs and firecrawl/skills has 5,700. They score 0.79–0.80 against each other, with the same intent.
  12. Keep both, because they are separate repos. Give each a different angle: which repo it comes from and how it is installed. If a person confirms the two are identical copies, use a canonical to firecrawl/cli instead.

Pairs and recommendations

Scores are cosine similarity from semantic_search, a search on the H1 of the first page. Each page has only one embedded section, and that section is the title sentence. So "best matching sections" here compares the title boilerplate, not the body text. The intent verdicts are my judgment from skill names and publishers.

PairScoreSame intent? (my judgment)Action
claude-seo/seo ↔ seo-technical0.765Partly. The first is a general entry point and the second is technical checks.Keep both. Angle: overview and router vs technical checks only.
claude-seo/seo-audit ↔ seo-technical0.783Partly. An audit includes technical checks.Keep both. Angle: full-site audit report vs technical-fix checklist.
claude-seo/seo ↔ seo-audit0.756No.Do nothing beyond the template fix.
firecrawl/cli ↔ firecrawl/skills firecrawl-crawl0.786–0.800YesKeep both with different angles, or set a canonical (see change 3).
gws-workflow ↔ gws-workflow-file-announce0.746No. The first is the parent hub and the second is one task.Keep both. Angle: hub that lists workflows vs file announcements.
gws-workflow ↔ gws-workflow-weekly-digest0.743No. Same hub-versus-task relationship.Keep both. Angle: hub vs weekly digest.
larksuite/cli ↔ open.larksuite.com ↔ open.feishu.cn, lark-workflow-meeting-summary0.744–0.778YesSet a canonical (change 2).
Same three, lark-workflow-standup-report0.759–0.793YesSet a canonical (change 2).

The nearest page for each of the six pages in the two Lark skills came from the sibling searches. I did not search the four open.* pages separately.

What I did not cover

  • Search Console: no Search Console tool is available here. I could not check which pairs share clicks on a query, so I have not marked any pair.
  • Body content: the pages have one embedded section each, so I could not compare body text. Pages with the same name but different publishers, and the hub-versus-task pairs, need a person to read them before the canonical or merge steps.
  • Searches run: 10 of 14. The 4 open.* pages were covered through their sibling pages, as noted above.
  • Fix list: the cannibal fix has 14 URLs and all 14 were returned, so nothing was cut. I did not call explain_fix. I did not create Jira tasks.

Appendix: the 14 URLs and their nearest page

  • /skills/agricidaniel/claude-seo/seo → seo-technical (0.765)
  • /skills/agricidaniel/claude-seo/seo-audit → seo-technical (0.783)
  • /skills/agricidaniel/claude-seo/seo-technical → seo (0.764)
  • /skills/firecrawl/cli/firecrawl-crawl → firecrawl/skills/firecrawl-crawl (0.787)
  • /skills/firecrawl/skills/firecrawl-crawl → firecrawl/cli/firecrawl-crawl (0.798)
  • /skills/googleworkspace/cli/gws-workflow → gws-workflow-email-to-task (0.754). That page is not in the cannibal list, but file-announce (0.744) and weekly-digest (0.742) are the next nearest.
  • /skills/googleworkspace/cli/gws-workflow-file-announce → gws-workflow (0.746)
  • /skills/googleworkspace/cli/gws-workflow-weekly-digest → gws-workflow (0.743)
  • /skills/larksuite/cli/lark-workflow-meeting-summary → open.larksuite.com (0.778). I read this one from the open.larksuite.com search, where it scored 0.7784 against its own H1.
  • /skills/larksuite/cli/lark-workflow-standup-report → open.larksuite.com (0.793). I read this one from the open.larksuite.com standup-report search, where it scored 0.793.
  • /skills/open.feishu.cn/lark-workflow-meeting-summary, .../lark-workflow-standup-report, /skills/open.larksuite.com/lark-workflow-meeting-summary and .../lark-workflow-standup-report → the same-name page on larksuite/cli, from the sibling searches.
B17

Search Console × rastreo: victorias rápidas

Victorias rápidas con demanda real (requiere una herramienta de Search Console en el agente).

/gsc-opportunities*

Herramientas de GLLmolfar que llama: semantic_searchget_pagesaudit_url

Rellenas: min_impressions

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

* 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.

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.

Qué ha cambiado
en esta versión.

La app muestra estas mismas notas cuando sale una versión nueva, así ves qué cambia antes de actualizar.

  • Cambios en sitemaps, en Proyectos: añade cualquier sitio y la app lee sus sitemaps públicos según un horario, cuenta las páginas y muestra lo nuevo o lo eliminado desde la última revisión
  • Exportar las páginas de un sitemap requiere una cuenta con sesión iniciada; las revisiones y los recuentos funcionan sin ella
  • El neuro-pipeline vuelve a animar los fragmentos mientras se crean, no solo cuando algo frena la ejecución
  • Búsqueda semántica: el título y la dirección de cada resultado vuelven a leerse bien

Qué
esperar.

Alcance, método y límites de la preview actual.

Al descargar aceptas los términos de la preview de GLLmolfar.

¿Qué hace un rastreo?

Pide las URL del sitio que eliges, sigue el método de descubrimiento y el alcance que definas, registra cada respuesta y extrae datos de páginas y enlaces para los informes. No modifica las páginas del sitio.

¿Cómo ayuda con la búsqueda con IA, GEO y AI Overviews?

Revisa la base: si robots.txt permite a cada rastreador de IA descargar el sitio, si existe llms.txt y si las páginas se dividen en fragmentos que un asistente puede citar por sí solos. La búsqueda semántica y la vista de fragmentos muestran qué páginas responden a una pregunta por significado. No mide si los asistentes te citan o mencionan de verdad.

¿En qué se diferencia Spider + sitemap de solo Spider?

Spider sigue los enlaces que encuentra en el HTML de las páginas. Spider + sitemap también lee los sitemaps XML y registra qué páginas descubiertas aparecen en ellos. Solo Sitemap empieza por las URL del sitemap; el modo lista revisa solo las URL que proporcionas.

¿Qué pasa al activar el renderizado de JavaScript?

En modo Auto, las páginas con menos de 100 palabras en su HTML original se abren en un navegador integrado y se revisan de nuevo tras ejecutar JavaScript. También puedes renderizar todas las páginas o desactivar el renderizado. Es un diagnóstico de rastreo, no una garantía de que las defensas antibots o el comportamiento del navegador coincidan con Google.

¿Cómo funciona el análisis de temas?

La app divide el texto de las páginas en fragmentos, los convierte en vectores con un modelo local de embeddings y compara esos vectores para agrupar páginas y fragmentos relacionados. Las etiquetas de los grupos se basan en términos distintivos. El modelo no escribe recomendaciones ni textos.

¿Detecta la canibalización de palabras clave?

De dos maneras. A partir del rastreo, marca páginas del mismo idioma inusualmente parecidas por su significado y muestra la evidencia en paralelo: una pista de solapamiento de contenido que conviene revisar. Con Search Console conectado, lista las consultas para las que Google mostró de verdad dos o más de tus páginas, cada una con una parte real de las impresiones, primero la página con más clics. La primera no necesita datos de Google; la segunda es lo que hizo realmente la búsqueda.

¿Cómo se conecta Search Console y qué ve?

Inicia sesión en la app con Google, abre Search Console en la barra lateral y pulsa Conectar Search Console. Solo se puede conectar esa misma cuenta de Google y solo con acceso de lectura a Search Console. getlooploop.com guarda el permiso de acceso cifrado; los informes viajan de Google a tu equipo y se guardan allí, así que el último se ve, con su fecha, sin conexión o sin sesión. Pulsar Desconectar o cerrar sesión en la app borra el permiso, no los informes.

¿Qué se queda en mi equipo?

Los registros y el historial de rastreos se guardan en una base de datos SQLite local. Los embeddings se calculan en tu equipo tras descargar el modelo. La app sigue enviando peticiones web normales al sitio que rastreas; la revisión opcional de enlaces externos también pide esas URL, y los datos del dominio se consultan en servicios públicos de RDAP, WHOIS y DNS. Al arrancar lee un archivo público de versión en getlooploop.com para avisarte de actualizaciones, y envía estadísticas de uso anónimas: un ID de instalación aleatorio que crea la propia app, la versión, la versión de Windows o macOS, el idioma de la interfaz y cuándo se abrió y se cerró. Nunca una URL, un dominio ni nada de un rastreo. Ambas cosas se desactivan en Ajustes. Con Search Console conectado, la app lee la API de Google directamente; getlooploop.com guarda solo el permiso de acceso cifrado.

¿Cuáles son los límites actuales?

Sin cuenta, un rastreo lee hasta 5.000 URL; con una cuenta gratuita, 50.000; los niveles de pago llegan a 1.000.000, el techo de la propia app. Así funciona ahora: es una intención, no una promesa; los límites pueden cambiar y cambiarán. El sitemap puede contener más URL que el límite: el límite se aplica a las páginas descargadas, no a las entradas del sitemap que se leen.

¿Cómo funcionan las actualizaciones?

Mientras la app está abierta, busca una versión nueva cada media hora. En Windows descarga la actualización en segundo plano, compara su SHA-256 con el archivo publicado y muestra un botón rojo de reinicio en la barra de título; la actualización se instala al reiniciar, con los rastreos y los ajustes intactos. En Mac te avisa de la versión nueva y abre la página de descarga. La búsqueda de actualizaciones se puede desactivar en Ajustes.

Dónde está,
con honestidad.

Dos rastreadores SEO conocidos, sin nombrarlos, junto a la preview gratuita de GLLmolfar. Donde ellos hacen más, la tabla lo dice.

SíEn parte: ver la notaNoGLLmolfarCompetidor 1Rastreador de escritorioCompetidor 2Auditor de escritorio y nube
Para empezar
Versión gratuita5.000 URL por rastreo, 50.000 con una cuenta gratuita**500 URL por rastreoNoSolo prueba de 14 días
Rastreo más grandeHasta 1.000.000 URL en niveles de pago**Sin límite fijo*Hasta 10 millones de URL (en la nube)
Funciona en tu equipoSíSíSí
Windows y MacWindows 10+, Mac con Apple siliconWindows, macOS, UbuntuWindows 10/11, macOS Sonoma+
SEO técnico
Enlaces rotos, redirecciones, títulos, directivas, hreflangSíSíTambién en la versión gratuitaSí
Renderizado de JavaScriptSíAutomático en páginas con poco textoSíVersión de pagoSí
Historial y comparación de rastreosSíSíVersión de pagoSí
Rastreos programadosSíIncluidoSíVersión de pagoSí
Search Console y AnalyticsEn parte: ver la notaSearch Console, nueve informes, gratis con sesión iniciada; sin AnalyticsSíVersión de pagoSí
Estado de indexación en Google, URL a URL (URL Inspection)SíGuardado en tu equipo; los 2.000 diarios de Google, por partesSíVersión de pagoSíLas 2.000 URL HTML con más enlaces internos, al día
Auditoría de accesibilidadEn parte: ver la notaCon el HTML de cada página; aún sin contrasteSíVersión de pagoSí
Exportar a Google SheetsSíA tu propio Drive; la app solo ve los archivos que creaSíSíSubida automática en Pro
Bots de IA, cada uno con su grupo de robots.txtSíPresets de GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot y PerplexityBotEn parte: ver la notaCualquier agente que escribas; sin presets de IA documentadosEn parte: ver la notaCualquier agente que escribas; presets solo de buscadores
User agent e IP pública del rastreo en pantallaSíEn directo durante el rastreo y en la tarjeta del proyectoNoEn parte: ver la notaDirección IP en Settings › Logging
Significado y búsqueda con IA
Temas agrupados por significadoSíIncluido, gratisEn parte: ver la notaDe pago, con tu propia clave de un proveedor de IANoNo disponible
Canibalización por significadoSíIncluido, gratisEn parte: ver la notaDe pago, con tu propia clave de un proveedor de IANoSolo casi-duplicados por palabras
El texto de las páginas no sale de tu equipo durante el análisis con IASíModelo de embeddings localEn parte: ver la notaSolo con un servidor de IA local propioNoLa IA trabaja en un asistente de chat con datos exportados
Gráficos de consultas de Search ConsoleSíPalabras de consultas como treemap, gráficos de posición y CTRNoEn parte: ver la notaClics y CTR por posición, marca aparte
Mapa de atención sobre la captura de una páginaSíUna previsión por el diseño, rotulada como talNoNo
Agentes de IA por MCPSíServidor local; puede lanzar rastreosSíDe pago; puede lanzar rastreosEn parte: ver la notaLee auditorías terminadas; no lanza rastreos
Una corrección como tarea de JiraSíUn botón en cada corrección, y para agentesNoEn parte: ver la notaCon su skill de MCP en tu asistente de IA

Los competidores no se nombran. Sus marcas salen de sus propias páginas de funciones y documentación, consultadas en octubre y noviembre de 2026; las funciones cambian, así que compruébalo con el fabricante antes de decidir.

* Limitado por la memoria y el disco del equipo.

** Los límites de GLLmolfar tal como funcionan ahora: una intención, no una promesa. Pueden cambiar y cambiarán.

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