Todos los Skills / PROBABL-AI

probabl-ai/skore-skills

choose-python-library

Resolve a library choice and add the selected dependency.

Ver código fuente

Cómo usar

Copia el comando y revisa el paquete antes de instalarlo en tu entorno de agente.
Consulta las herramientas, credenciales y entornos necesarios en el documento original.
Describe las entradas y el resultado deseado; contrasta la salida con las fuentes.

npx skills add https://github.com/probabl-ai/skore-skills --skill choose-python-library

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.

Choose Python Library

Human-facing prose

Details: setup-workspace references/human_facing_prose.md. Present library options as a data-science choice for this job. Do not name skill ids or the wrapper CLI in the question.

State the job and constraints.
Run python -m skore_skills env stack. A job listed under

competing is a genuine choice; anything the policy already fixes (mandatory, stage, export) is settled — use it rather than reopening the choice. Do not read the packaged JSON file directly; it lives inside the installed package.

For a genuine choice, present the smallest useful option set and

ask the user. Do not pick silently.

After the user chooses, load add-python-package when

status.skills reports it installed. If it is not installed, name the package and stop. Do not call env add from this skill. Typical callers: explore-ml-data (pandas vs polars), later extras (tuning). Not setup-workspace. Plotting jobs: load plot-ml-figure if installed; do not present matplotlib vs seaborn vs plotly.

Confirm symbols with python -m skore_skills api get <dotted>...

before writing calls. Several symbols go in one call. Scope for one package is python -m skore_skills env route <pkg>, not a guess.

Stop conditions

Do not install every candidate.
Do not use popularity alone as a technical decision.
Do not run pip directly in a managed project.
Do not substitute black/isort for Ruff or sklearn Pipeline for

skrub DataOps; those choices are already fixed.

Do not present matplotlib vs seaborn vs plotly; that job is

plot-ml-figure.

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