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 preparar-a-un-entrevistadorgit 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/preparar-a-un-entrevistador)<a href="https://agentmods.dev/skills/gethouston/houston/preparar-a-un-entrevistador"><img src="https://agentmods.dev/badge/skills/gethouston/houston/preparar-a-un-entrevistador/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/preparar-a-un-entrevistador"><img src="https://agentmods.dev/badge/skills/gethouston/houston/preparar-a-un-entrevistador.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 | $0.00069 | $0.01639 |
| Opus 5 | $0.00034 | $0.00820 |
| Sonnet 5 | $0.00014 | $0.00328 |
| Haiku 4.5 | $0.00007 | $0.00164 |
Grade A, and why
preparar-a-un-entrevistador 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 — 124 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Preparar a un Entrevistador
Cuándo usarla
- Explícito: "prepárame para entrevistar a {candidate}", "qué le pregunto a {candidate}", "resumen de entrevista para {candidate}", "prepárame para el proceso de {candidate}".
- Implícito: llamada como dependencia por
coordinar-un-proceso-de-entrevistas, cada panelista necesita un resumen a la medida. - Una invocación equivale a un resumen para un entrevistador. ¿Todo
el panel? Se llama una vez por entrevistador vía
coordinar-un-proceso-de-entrevistas.
Conexiones que necesito
Realizo el trabajo externo a través de Composio. Antes de correr esta habilidad, 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.
- Documentos (Notion, Google Docs): leer rúbricas de entrevistas previas o compartir el resumen si las guardas en un espacio de trabajo compartido. Opcional.
- Extracción web (LinkedIn): actualizar datos de antecedentes desde un perfil público si el registro del candidato está escaso. Opcional.
- Bandeja de entrada (Loops o Gmail): obtener contexto previo de hilos con el candidato para el resumen del entrevistador. Opcional.
Esta habilidad lee sobre todo archivos locales, así que las conexiones faltantes no me detienen, simplemente trabajo con lo que ya está en el registro del candidato.
Información que necesito
Primero leo tu contexto de personal. Por cada campo obligatorio que falte, hago UNA pregunta en lenguaje sencillo (mejor modalidad: app conectada > archivo > URL > texto pegado) y espero.
- Registro del candidato: Obligatorio. Por qué lo necesito: cada afirmación del resumen debe rastrearse hasta él. Si falta, pregunto: "Primero haz una evaluación de este candidato soltando el currículum o compartiendo la URL de LinkedIn, para que tenga algo de dónde partir."
- Rúbrica del puesto: Obligatoria. Por qué la necesito: califico las preguntas de la entrevista contra tus imprescindibles. Si falta, pregunto: "¿Para qué puesto es este candidato, y cuáles son tus tres principales imprescindibles?"
- Nombre del entrevistador y área de enfoque: Obligatorios. Por qué los necesito: cada panelista es dueño de criterios distintos de la rúbrica. Si faltan, pregunto: "¿Quién lleva esta entrevista, y cuál es su enfoque: técnico, sistemas, liderazgo, o valores?"
- Marco de niveles: Obligatorio. Por qué lo necesito: la rúbrica de puntaje se ata al estándar de este nivel. Si falta, pregunto: "¿Para qué nivel estamos contratando, y cómo describirías qué significa 'cumplir el estándar' en ese nivel?"
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 · 124 lines · 69 tokens per session scan A 9aecfb547146
preparar-a-un-entrevistador is a skill published in the GitHub repository gethouston/houston (113 stars, last pushed today), licensed MIT. It adds 69 tokens to every session and 1,639 once invoked, about $0.0003 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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