probabl-ai/skore-skills

review-ml-choices

Show stored project choices and re-enter the skill that can change one.

Vedi sorgente

Come usare

  1. Copia il comando e controlla il pacchetto prima di installarlo nel tuo ambiente agente.
  2. Controlla strumenti, credenziali e ambienti richiesti nel documento originale.
  3. Descrivi input e risultato desiderato; confronta l’output con le fonti.
npx skills add https://github.com/probabl-ai/skore-skills --skill review-ml-choices

Prima di iniziare

  • L’installazione non include abbonamenti, quote API o accesso ai file.
  • Stelle e installazioni indicano attività, non un test indipendente di qualità o sicurezza.
Documento Skill originale

Contenuto dal repository con titoli, esempi, codice, tabelle, link e immagini preservati.

Review ML Choices

Show stored choices. A change loads the skill that already owns that decision. Do not write .skore or the journal from here.

Human-facing prose

Details: setup-workspace references/human_facing_prose.md. The board uses data-science labels: where reports go, executed notebooks, documentation site, git commits, who manages the environment, data analysis, and each filled framing cell (prediction goal, deployment, metric, fold count, and the others below). Do not put skill ids, G-* names, or the wrapper CLI in the question.

Sequence

  1. Run python -m skore_skills review choices. The JSON is the

board. Do not rebuild which rows are offered. Do not run frame show or frame clear here.

  1. AskUserQuestion, one pick. Say first, in 2–4 lines, what a

change authorizes — re-entering that setup, not a silent flag flip — and echo the current values from the JSON. A file link is an addition, never the context.

Options are Keep these plus one option per changeable row and one option per framing row. read_only and not_offered are context, not options. Use each row's value. For not_offered, say that row's reason. When framing_reason is set, say it and do not offer framing rows. "Who manages the environment" is whether this project manages it (policy.env.managed). An installed skill is not that value. Do not write a skill id on the board.

  1. Keep these → stop. Do not load a skill.
  2. One changeable row → load that row's skill and stop. The

close names the decision being re-opened, not the skill id. Do not policy set. Do not run the child's commands from memory.

  • skore_mode → the user asked to change where reports go.
  • notebooks_site → notebooks and the documentation site.
  • git_autocommit → the user asked to change that choice.
  • env_managed → do not run env add-skore here. If the

recorded destination is hub or mlflow, do not use --mode local.

  • data_analysis when action is rerun → do not write a

JOURNAL skipped row. The written analysis stays; the change is to run it again.

  1. One framing row → load frame-ml-problem naming that

row's id. Do not blank the cell here.

  1. A request to change a read_only row: say that row's

reason and stop. Do not load setup-workspace to rename. Do not policy set.

Stop conditions

  • Do not policy set any key.
  • Do not edit JOURNAL, including a Data understanding skipped

row.

  • Do not load sync-ml-reports when policy.skore_mode is

unset.

  • Do not env add-skore, git commit, or scaffold src/.
  • If the owning skill is not installed, show the value and skip

the change in one line. Do not invent that skill's steps.

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