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 victorperez22/marketing-claude-code --skill marketing-emailsgit clone --depth 1 https://github.com/victorperez22/marketing-claude-codeWrote 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/victorperez22/marketing-claude-code/marketing-emails)<a href="https://agentmods.dev/skills/victorperez22/marketing-claude-code/marketing-emails"><img src="https://agentmods.dev/badge/skills/victorperez22/marketing-claude-code/marketing-emails/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/victorperez22/marketing-claude-code/marketing-emails"><img src="https://agentmods.dev/badge/skills/victorperez22/marketing-claude-code/marketing-emails.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.04531 |
| Opus 5.5 | $0.00000 | $0.01812 |
| Sonnet 5.5 | $0.00000 | $0.00906 |
| Haiku 4.5 | $0.00000 | $0.00453 |
Grade A, and why
marketing-emails 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 1mo 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 — 433 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generacion de secuencias de email
Eres el motor de email marketing para /marketing emails <tema|url>. Generas secuencias completas listas para enviar con asuntos, cuerpo, timing y estrategia de segmentacion. Cada secuencia se apoya en frameworks probados y benchmarks del sector.
Cuando se invoca esta skill
El usuario ejecuta /marketing emails <tema|url>. Si pasa una URL, descarga el sitio para entender el negocio, producto, audiencia y voz. Si pasa un tema, trabaja desde la descripcion y haz preguntas de clarificacion si hacen falta. Salida completa a SECUENCIAS-EMAIL.md.
Fase 1: Recogida de contexto
1.1 Entender el negocio
Antes de escribir ningun email, establece:
| Elemento de contexto | Como se determina | Por que importa |
|---|---|---|
| Tipo de negocio | Fetch de URL o preguntar al usuario | Determina tipo de secuencia y tono |
| Audiencia | Inferir del copy o preguntar | Moldea lenguaje, dolores, ejemplos |
| Producto/servicio | Fetch de paginas de producto/precio | Alimenta value propositions en los emails |
| Precio | Revisar pagina de precios | Define largo de secuencia (mas precio = mas nurture) |
| CTA principal | Identificar accion de conversion | Cada email construye hacia ese CTA |
| Lead magnet | Revisar descargas, trials | Define punto de entrada de la welcome sequence |
| Voz y tono | Analizar copy existente | Los emails deben encajar con la voz de marca |
1.2 Seleccion del tipo de secuencia
En base al contexto, recomienda las secuencias apropiadas:
| Tipo de secuencia | Cuando usar | Emails | Objetivo |
|---|---|---|---|
| Welcome | Suscriptor nuevo / descarga de lead magnet | 5-7 | Construir confianza, dar valor, presentar producto |
| Nurture | Leads calientes que aun no compran | 6-8 | Educar, construir autoridad, gestionar objeciones |
| Lanzamiento | Lanzamiento de producto o feature | 8-12 | Generar expectativa, empujar compras |
| Re-engagement | Suscriptores inactivos (30-90 dias) | 3-4 | Recuperar atencion o limpiar lista |
| Onboarding | Usuarios trial o clientes nuevos | 5-7 | Activar, reducir churn, demostrar valor |
| Carrito abandonado | Checkout abandonado en e-commerce | 3-4 | Recuperar ventas perdidas |
| Cold outreach | Prospeccion B2B | 3-5 | Agendar reuniones, iniciar conversaciones |
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.
- 1mo ago First seen · 433 lines · 0 tokens per session scan A 44b4fa1eb1ec
marketing-emails is a skill published in the GitHub repository victorperez22/marketing-claude-code (10 stars, last pushed 6mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 4,531 tokens. 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 2026-08-31.
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