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.
npx skills add gethouston/houston --skill planear-una-campanagit clone --depth 1 https://github.com/gethouston/houstonWrote 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.
[](https://agentmods.dev/skills/gethouston/houston/planear-una-campana)<a href="https://agentmods.dev/skills/gethouston/houston/planear-una-campana"><img src="https://agentmods.dev/badge/skills/gethouston/houston/planear-una-campana/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.
<a href="https://agentmods.dev/skills/gethouston/houston/planear-una-campana"><img src="https://agentmods.dev/badge/skills/gethouston/houston/planear-una-campana.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00092 | $0.03085 |
| Opus 5 | $0.00046 | $0.01543 |
| Sonnet 5 | $0.00018 | $0.00617 |
| Haiku 4.5 | $0.00009 | $0.00309 |
Grade A, and why
planear-una-campana 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Planear una campaña
Una sola skill, toda especificación de campaña. El parámetro type elige la forma; posicionamiento, voz, cliente ideal y "solo borradores, sin tácticas de culpa" son compartidos.
Parámetro: type
paid: audiencia + palabras clave/ubicación + estructura de grupos de anuncios + presupuesto + requisito de landing page + KPIs.launch: plan de 2 semanas secuenciado Día -7 → Día 0 → Día +7, cada tarea etiquetada con la skill de ESTE agente que la ejecuta.lifecycle-drip: secuencia automatizada por evento con disparador + evento meta + reglas de frecuencia + ramificación según la acción del usuario + correos redactados.welcome: serie de 5 correos para nuevos registros (por defecto Día 0 / 1 / 3 / 7 / 14, puedes anular cualquier cadencia).churn-save: correo de retención que ofrece UNA sola opción genuina (pausa / downgrade / atención personalizada / reembolso). Sin tácticas de culpa.announcement: copy de correo + copy correspondiente dentro de la app (banner + modal + aviso en estado vacío), todo alineado al mismo CTA principal.
Tú nombras el tipo en lenguaje simple, yo lo infiero. Si es ambiguo, hago UNA pregunta nombrando las 6 opciones.
Cuándo usarlo
- Explícito: "planea una campaña paga en {channel}", "planea el lanzamiento de {feature}", "diseña una secuencia para {segment}", "redacta una serie de bienvenida", "correo de retención para {account}", "redacta el anuncio de {feature}".
- Implícito: me llaman después de
audit-a-surface(landing-page / site-seo) cuando el fundador está listo para invertir presupuesto detrás de una página ya corregida.
Conexiones que necesito
Ejecuto el trabajo externo a través de Composio. Antes de correr esta skill, reviso que las categorías de abajo estén conectadas. Si falta alguna, te digo cuál es, te pido que la conectes desde la pestaña de Integraciones y me detengo.
- Plataforma de correo (Customer.io, Loops, Mailchimp, Kit, etc.): redacta correos de drip / bienvenida / retención / anuncio en tu remitente. Obligatoria para
lifecycle-drip,welcome,churn-save,announcement. - Plataformas de anuncios (Google Ads, Meta Ads, LinkedIn Ads): trae la forma de tu cuenta, audiencia y palabras clave para que el brief encaje con tu cuenta real. Obligatoria para
paid(el canal que estás planeando). - CRM (HubSpot, Salesforce, Attio): segmenta audiencias y trae disparadores de comportamiento. Opcional, pero mejora la precisión de la segmentación.
- Facturación (Stripe): marca señales de downgrade y cancelación para
churn-save. Obligatoria parachurn-save.
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.
- 12d ago First seen · 85 lines · 92 tokens per session scan A 922419b9ebd9
planear-una-campana is a skill published in the GitHub repository gethouston/houston (113 stars, last pushed today), licensed MIT. It adds 92 tokens to every session and 3,085 once invoked, about $0.0005 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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