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probabl-ai/skore-skills

choose-python-library

Resolve a library choice and add the selected dependency.

Voir la source

Mode d’emploi

  1. Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
  2. Consultez le document original pour les outils, identifiants et environnements requis.
  3. Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/probabl-ai/skore-skills --skill choose-python-library

Avant de commencer

  • L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
  • Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original

Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.

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.

  1. State the job and constraints.
  2. 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.

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

ask the user. Do not pick silently.

  1. 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.

  1. 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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Answer questions about ECC by reading the live repo surface — agents, skills, commands, hooks, rules, install profiles, and docs — instead of memory. Use when the user asks what ECC includes, how to install or reset it, which skill or command fits a task, or how project onboarding works.

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Pythonic idioms, PEP 8 standards, type hints, and best practices for building robust, efficient, and maintainable Python applications. Use when writing or reviewing Python code and idiomatic structure, typing, or PEP 8 is in question.

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