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 calibrar-mi-vozgit 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/calibrar-mi-voz)<a href="https://agentmods.dev/skills/gethouston/houston/calibrar-mi-voz"><img src="https://agentmods.dev/badge/skills/gethouston/houston/calibrar-mi-voz/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/calibrar-mi-voz"><img src="https://agentmods.dev/badge/skills/gethouston/houston/calibrar-mi-voz.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 | $0.00060 | $0.01802 |
| Opus 5 | $0.00030 | $0.00901 |
| Sonnet 5 | $0.00012 | $0.00360 |
| Haiku 4.5 | $0.00006 | $0.00180 |
Grade A, and why
calibrar-mi-voz 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 — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Calibrar Mi Voz
Ofertas, rechazos, anuncios al equipo, planes de mejora de desempeño
(PIP), conversaciones de retención: toda habilidad que este agente
redacta se apoya en tu voz. Esta habilidad revisa cómo escribes de
verdad las comunicaciones de Recursos Humanos y guarda la huella de
tono en context/people-context.md, de donde parte cada borrador
posterior.
Cuándo usarla
- "calibra mi voz de Recursos Humanos" / "revisa mis ofertas pasadas" / "aprende cómo escribo para Recursos Humanos".
- "actualiza las notas de voz en el documento de contexto de personal".
- Llamada implícitamente por
configurar-mi-informacion-de-personalcuando la sección de notas de voz está incompleta o desactualizada.
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.
- Bandeja de entrada (Gmail, Outlook): revisar tus mensajes enviados relacionados con Recursos Humanos. Obligatoria si quieres que saque ejemplos de ahí.
Si no hay bandeja de entrada conectada, pregunto una vez si prefieres que revise una bandeja conectada o que pegues de tres a cinco ejemplos.
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.
- Muestras de voz: Obligatorio. Por qué las necesito: cada punto de la huella de voz debe rastrearse hasta muestras reales. Si faltan, pregunto: "Conecta tu bandeja de entrada para que pueda sacar de 10 a 20 mensajes recientes de Recursos Humanos, o pega de tres a cinco ejemplos aquí."
- Alcance de las muestras: Opcional. Por qué lo necesito: me permite filtrar entre comunicaciones con candidatos o con el equipo. Si no lo tienes, sigo adelante con el conjunto más amplio de comunicaciones de Recursos Humanos que encuentre.
- Muestras de noticias difíciles: Opcional. Por qué las necesito: los rechazos y las aperturas de PIP suenan distinto a las notas de celebración. Si no las tienes, sigo adelante marcando la huella de noticias difíciles como pendiente.
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 · 155 lines · 60 tokens per session scan A 1b90fb42e1cb
calibrar-mi-voz is a skill published in the GitHub repository gethouston/houston (113 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 1,802 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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