oxbshw/watch-skill

learning-from-mistakes

The user corrected an answer about a video — "no, it actually says X", "that's the wrong timestamp", "you misread the error code" — or asks why a video answer was wrong.

Ver código fuente

Cómo usar

  1. Copia el comando y revisa el paquete antes de instalarlo en tu entorno de agente.
  2. Consulta las herramientas, credenciales y entornos necesarios en el documento original.
  3. Describe las entradas y el resultado deseado; contrasta la salida con las fuentes.
npx skills add https://github.com/oxbshw/watch-skill --skill learning-from-mistakes

Antes de empezar

  • La instalación no incluye suscripción al modelo, cuota API ni permisos sobre tus archivos.
  • Las estrellas e instalaciones reflejan actividad, no una prueba independiente de calidad o seguridad.
Documento original del Skill

Contenido del repositorio de origen con títulos, ejemplos, código, tablas, enlaces e imágenes preservados.

Learning from mistakes

When a video answer turns out wrong, the correction is worth more than an apology. Report it and Watch Skill learns locally — the mistake is classified, stored as a lesson, injected into future similar questions, and where possible the original question is immediately re-asked to confirm the lesson actually fixes it.

Report a correction

The moment the user corrects a video answer, run:

bash
watch-skill lessons add <video_id> "<question>" "<the wrong answer>" "<the correction>"

The output includes the lesson (error_class, guidance) and, when the question was re-asked, whether the corrected answer now comes back — tell the user which it was. Nothing is uploaded; lessons live in ~/.watch-skill/.

See what has been learned

bash
watch-skill lessons list

The savings meter

bash
watch-skill stats

Lifetime token economics: what text-first answering and the semantic cache have saved versus stuffing raw frames into context. Quote real numbers from it when the user asks whether any of this is worth it.

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