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 convertir-comentarios-de-linkedin-en-prospecciongit 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/convertir-comentarios-de-linkedin-en-prospeccion)<a href="https://agentmods.dev/skills/gethouston/houston/convertir-comentarios-de-linkedin-en-prospeccion"><img src="https://agentmods.dev/badge/skills/gethouston/houston/convertir-comentarios-de-linkedin-en-prospeccion/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/convertir-comentarios-de-linkedin-en-prospeccion"><img src="https://agentmods.dev/badge/skills/gethouston/houston/convertir-comentarios-de-linkedin-en-prospeccion.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 | $0.00146 | $0.02476 |
| Opus 5 | $0.00073 | $0.01238 |
| Sonnet 5 | $0.00029 | $0.00495 |
| Haiku 4.5 | $0.00015 | $0.00248 |
Grade A, and why
convertir-comentarios-de-linkedin-en-prospeccion 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 9d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Convertir comentarios de LinkedIn en prospección
Orquestador de principio a fin: entra la URL de una publicación de LinkedIn, sale una campaña de Instantly en pausa. Encadeno las cinco subhabilidades con un punto de control entre cada fase para que tú mantengas el control mientras el trabajo pesado ocurre automáticamente.
Úsala para comentaristas (mayor intención, menor volumen). Para quienes reaccionaron (5 a 10 veces más leads, con perfiles completos de LinkedIn adjuntos), usa en su lugar linkedin-reaction-to-outreach.
Cuándo usarme
- "Ejecuta el pipeline de LinkedIn sobre esta publicación: ".
- "Extrae y envía correos a estos comentaristas".
- "Prospección a partir de esta publicación de LinkedIn".
- Un ponente, competidor o líder de opinión publicó algo que le pega directo a tu perfil de cliente ideal, y quieres llegar a cada comentarista calificado en un solo movimiento.
Cuándo NO usarme
- Buscas a personas que reaccionaron a una publicación, usa
linkedin-reaction-to-outreach. Quienes reaccionan son de 5 a 10 veces más numerosos y traen datos de perfil más completos. - Solo necesitas la lista de comentaristas, sin prospección, usa
linkedin-comment-scraperdirectamente. - Solo necesitas enriquecer una lista existente, usa
apollo-enrichmentdirectamente. - Solo necesitas textos de correo en frío sin una fuente de leads, usa
cold-email-sequencedirectamente. - Ya tienes una lista verificada y los textos listos, usa
instantly-campaigndirectamente.
Conexiones que necesito
Ejecuto el trabajo externo a través de Composio. Antes de que esta habilidad corra, verifico que cada categoría de abajo esté conectada. Si falta alguna, nombro la categoría, te pido que la conectes desde la pestaña de Integraciones, y me detengo.
- Apify (scraping), para el actor de comentarios de LinkedIn. Obligatoria.
- Airtable (base de datos), para la tabla de seguimiento de leads. Obligatoria.
- Apollo (enriquecimiento), para emails verificados + empresa/cargo/ubicación. Obligatoria.
- Instantly (plataforma de envío), para la creación de la campaña y la carga de leads. Obligatoria.
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.
- 9d ago First seen · 127 lines · 146 tokens per session scan A 66de0b72a2c4
convertir-comentarios-de-linkedin-en-prospeccion is a skill published in the GitHub repository gethouston/houston (113 stars, last pushed yesterday), licensed MIT. It adds 146 tokens to every session and 2,476 once invoked, about $0.0007 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 2026-09-03.
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