auditar-una-superficie

auditar-una-superficie is a skill for Claude Code, Codex from gethouston/houston. It costs 84 tokens per session (2,841 once invoked), scanned A, original, MIT.

A marketing audit workflow that reviews one selected area: website SEO, visibility in AI search tools, a landing page, or a lead form.

In plain words
What is it for?
Use it to audit technical and content SEO, visibility in ChatGPT or similar search tools, landing-page quality, or unnecessary friction in demo, contact, lead, or checkout forms.
Why use it?
It turns a broad request for feedback into a focused review with specific findings and a priority order for fixes. Each area uses a different kind of check.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to audit technical and content SEO, visibility in ChatGPT or similar search tools, landing-page quality, or unnecessary friction in demo, contact, lead, or checkout forms.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gethouston/houston/auditar-una-superficie
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add gethouston/houston --skill auditar-una-superficie
Clone the repo
git clone --depth 1 https://github.com/gethouston/houston

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for auditar-una-superficie

README.md
[![agentmods](https://agentmods.dev/badge/skills/gethouston/houston/auditar-una-superficie/github.svg)](https://agentmods.dev/skills/gethouston/houston/auditar-una-superficie)
Your own site
<a href="https://agentmods.dev/skills/gethouston/houston/auditar-una-superficie"><img src="https://agentmods.dev/badge/skills/gethouston/houston/auditar-una-superficie/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for auditar-una-superficie

Your own site · 80×15
<a href="https://agentmods.dev/skills/gethouston/houston/auditar-una-superficie"><img src="https://agentmods.dev/badge/skills/gethouston/houston/auditar-una-superficie.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,841 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.02841
Opus 5 $0.00042 $0.01421
Sonnet 5 $0.00017 $0.00568
Haiku 4.5 $0.00008 $0.00284

Measured 12d ago against content hash 3846348d1610, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

auditar-una-superficie scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

store/agents-i18n/es/marketing/.agents/skills/auditar-una-superficie/SKILL.md · 192 lines

How it starts

The opening of the file, as written. The whole thing — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Auditar una superficie

Cuatro superficies de auditoría posibles. El parámetro surface elige la sonda;

Parámetro: surface

  • site-seo - auditoría on-page + técnica + de contenido del dominio configurado vía Semrush / Ahrefs / Firecrawl.
  • ai-search - sonda de visibilidad en ChatGPT / Perplexity / Gemini / Google AI Overviews + recomendaciones de GEO.
  • landing-page - obtiene la página vía Firecrawl, califica 6 dimensiones de 0 a 3, lista de arreglos priorizada.
  • form - marca campos innecesarios, reescribe etiquetas + texto de ayuda, ordena por fricción (formularios que no son de registro: demo / contacto / lead / checkout).

Mencionas la superficie en lenguaje simple ("auditoría SEO", "GEO", "hazme una crítica de mi landing page", "arregla mi formulario de demo") -> infiero. Si es ambiguo, hago UNA pregunta nombrando las 4 opciones.

Cuándo lo uso

  • Explícito: "haz una auditoría SEO", "audita mi visibilidad en buscadores con IA", "auditoría GEO", "critica {URL}", "audita mi formulario de leads".
  • Disparadores de ai-search: "¿aparezco en ChatGPT?", "¿somos visibles en Perplexity / Gemini para nuestra categoría?", "¿quién aparece cuando alguien pregunta sobre {categoría} en ChatGPT?".
  • Disparadores de form: "audita mi formulario de demo", "mi formulario de contacto está perdiendo gente", "este formulario de leads es muy largo, ¿qué puedo quitar?", "reescribe las etiquetas de este formulario", "revisa los campos del formulario de solicitud / checkout".
  • Implícito: dentro de plan-a-campaign (paid / launch) cuando la landing page enrutada necesita afinarse, o dentro de check-my-marketing (content-gap) cuando no se conoce la salud base del sitio.
  • Frecuencia por superficie: site-seo máximo semanal, ai-search máximo mensual, landing-page bajo demanda, form bajo demanda.

Conexiones que necesito

Ejecuto el trabajo externo a través de Composio. Antes de que corra este skill, verifico que las categorías de abajo estén conectadas. Si falta alguna, nombro la categoría, te pido que la conectes desde la pestaña de Integraciones, y me detengo.

Read the full file on GitHub · 192 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 192 lines · 84 tokens per session scan A 3846348d1610

Subscribe to this mod's changes

auditar-una-superficie is a skill published in the GitHub repository gethouston/houston (113 stars, last pushed today), licensed MIT. It adds 84 tokens to every session and 2,841 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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