Set Up Python Environment

Bootstrap only. Direct packages this turn: ruff, ipython, ipykernel, and plain skore. Skore supplies skore-skills as a mandatory dependency. Other stage libraries go through add-python-package.

Human-facing prose

Details: setup-workspace references/human_facing_prose.md. Ask which manager to use and whether we manage the env in plain language. Do not name G-ENV-MGR, skill ids, or the wrapper CLI to the user. Do not mention skore-skills.

Pre-flight

Tick, then immediately run the matching sequence step. Do not stop after listing the boxes.

- [ ] env detect + status
- [ ] G-ENV-MGR: ask if none / ambiguous / mismatch; else keep recorded
- [ ] env.managed: ask (default true) and persist
- [ ] unmanaged → stop | managed → env init, env sync, add-skore (no --mode), env verify

Not this skill

A request to add a package outside ruff, ipython, ipykernel, and plain skore is not bootstrap. Do not env init and do not pixi add. Hand that package to the package-install step and stop. The close names the package and that step in plain language. Do not write the catalog id.

Sequence

1. python -m skore_skills env detect and status.

2. G-ENV-MGR. Read the JSON fields, not sentinel strings: ask when env_manager is "none", ambiguous is true, or mismatch is true. Use recommended as the ask order. PATH is not permission. Do not curl | sh.

3. Ask whether we manage the env (default yes). Persist python -m skore_skills policy set env.managed true or false.

4. Unmanaged: stop. Name ruff / ipython / ipykernel / skore; do not init. Do not mention skore-skills to the user.

5. Managed: policy set env_manager <manager>, then

   python -m skore_skills env init --manager <manager>
   python -m skore_skills env sync --execute
   python -m skore_skills env add-skore --execute
   python -m skore_skills env verify --execute
   

   Do not pass --mode. Omitting it installs for a recorded hub or mlflow destination, and plain Skore otherwise.

   If the selected manager is pixi and pixi.toml already exists, skip env init; preserve that manifest and continue with env sync --execute. Never replace it or try to add [tool.pixi] to pyproject.toml.

   Do not hand-edit TOML. Do not run pixi init. Do not create src/. Do not ask where reports go. Plain Skore is the early install when no destination is recorded; add-python-package upgrades it for Hub or MLflow after that choice is recorded. Do not pass --mode local. If verify reports missing skore or skore_skills, rerun env add-skore --execute the same way; never add skore-skills directly. If verify reports missing agent tools, load add-python-package for ruff / ipython / ipykernel (agent feature) when that skill is installed, not a second env init. If add-python-package is not installed, name ruff / ipython / ipykernel and stop.

Return and close

When dispatched by setup-ml-project, return to that caller after verification. Standalone, run python -m skore_skills git end-turn --stage setup. If JSON action is invoke, load persist-ml-git only if status.skills.persist-ml-git is true and stop; that skill returns to triage. If persist is missing, name the pending staged paths and stop. Otherwise load triage-ml-task only if status.skills.triage-ml-task is true; else stop.

Three environments

Agent context only; do not narrate skore-skills to the user.

• default — project runtime; bootstrap installs plain skore, which supplies skore-skills, when the report destination is unset or local. A recorded hub or mlflow destination uses that install instead.
• agent — ruff, ipython, ipykernel.
• dev — default + agent. Every later python -m skore_skills command uses this composed environment; env verify --execute must pass before other skills run.