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 extraer-comentarios-de-linkedingit 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/extraer-comentarios-de-linkedin)<a href="https://agentmods.dev/skills/gethouston/houston/extraer-comentarios-de-linkedin"><img src="https://agentmods.dev/badge/skills/gethouston/houston/extraer-comentarios-de-linkedin/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/extraer-comentarios-de-linkedin"><img src="https://agentmods.dev/badge/skills/gethouston/houston/extraer-comentarios-de-linkedin.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 | $0.00105 | $0.01523 |
| Opus 5 | $0.00053 | $0.00762 |
| Sonnet 5 | $0.00021 | $0.00305 |
| Haiku 4.5 | $0.00011 | $0.00152 |
Grade A, and why
extraer-comentarios-de-linkedin 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 8d 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 — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Extractor de comentarios de LinkedIn
Extraigo a todas las personas que comentaron en una publicación de LinkedIn en una lista limpia y sin duplicados. Fase 1 del pipeline de comentarios a prospección, pero puedes ejecutarla de forma independiente si solo necesitas la lista (por ejemplo, como entrada para otra herramienta distinta más adelante).
Cuándo usarme
- "Extrae a quienes comentaron en esta publicación de LinkedIn: ".
- "Dame una lista de quién comentó en esta publicación".
- Quieres una lista limpia y sin duplicados de comentaristas para cualquier uso posterior, no necesariamente para prospección en frío.
Cuándo NO usarme
- Quieres a quienes reaccionaron a una publicación (no comentaron), usa
linkedin-reaction-scraper. - Quieres el pipeline completo de principio a fin hasta Instantly, usa
linkedin-comment-to-outreach.
Conexiones que necesito
- Apify (scraping), obligatoria. Uso el actor
harvestapi/linkedin-post-comments.
Si Apify no está conectado, me detengo y te pido que la conectes desde la pestaña de Integraciones.
Información que necesito
- La URL de la publicación de LinkedIn, obligatoria. Si falta, pregunto: "¿Qué publicación de LinkedIn extraigo?"
- Una cantidad objetivo de elementos, opcional. Por defecto usa
defaultMaxItemsde tu contexto de prospección (500). Puedes indicar otra por llamada si solo quieres una prueba rápida.
Pasos
-
Validar la URL. Confirmo que la URL sea de una publicación de LinkedIn (
linkedin.com/posts/...olinkedin.com/feed/update/...). Rechazo URLs de perfil, de artículo, de empresa. Si la entrada es un enlace corto o una redirección, la sigo una vez para resolver la URL canónica de la publicación antes de extraer. -
Extracción de prueba. Primera llamada al actor con
maxItems: 20para confirmar que la publicación es accesible y que el actor devuelve la forma esperada. Si la extracción de prueba devuelve 0 elementos, me detengo y explico por qué (publicación eliminada, comentarios deshabilitados, bloqueo geográfico, inicio en frío del actor).
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.
- 8d ago First seen · 88 lines · 105 tokens per session scan A fb7f0cf4fa6f
extraer-comentarios-de-linkedin is a skill published in the GitHub repository gethouston/houston (113 stars, last pushed today), licensed MIT. It adds 105 tokens to every session and 1,523 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 2026-09-03.
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