Loading...
Loading...
Found 2 Skills
Decide where files live in an ML experimentation project: reusable code in `src/<pkg>/`, one `# %%` script per experiment in `experiments/`, design notes + index in `journal/`, reports in `reports/`, agent-only probes in `scratch/`, narrative digest in `overview/summary.md`. Owns the layout, the file-creation rules (one file per experiment, ask before editing), and the jupytext `# %%` script convention. Never imposes `data/` — the user owns that. TRIGGER — any of: - Starting a new ML project / scaffolding a workspace. - About to create the first experiment file in a project. - About to create `src/<pkg>/data.py` / `features.py` / `pipeline.py` / `evaluate.py` for the first time. - About to write a `.ipynb` for experimentation — redirect to a `# %%` script under `experiments/`. - User asks where something should live, how to organize the project, or how to set up the workspace. - About to add a new experiment iteration — decide new file vs edit existing (ask the user). SKIP when: the file is clearly part of an already-populated module (e.g., adding a function to existing `features.py`); pure refactor inside a single existing file; pipeline declaration mechanics (`build-ml-pipeline`); evaluation mechanics (`evaluate-ml-pipeline`); skore symbol lookup (`python-api`). HOW TO USE: **first run the Detection table** below — if any signal matches, glue to existing conventions (do not rename or move folders). If no signal matches, scaffold the default layout. **Emit the Pre-flight checklist as visible text and read the Stop conditions before any file is created or edited.** Use templates in `templates/`; copy and adapt, do not rewrite from scratch.
Detect the env manager and bootstrap the runtime, agent-tools, and composed development environments. Detect with `python -m skore_skills env detect`, persist the manager and `env.managed`, then `env init --manager`, `env sync --execute`, install Skore for a recorded hub or mlflow destination (plain Skore when unset or local), and `env verify --execute`. Does not add other stage ML libraries. TRIGGER when the user asks for the env manager, pixi, uv, or a Python environment, or when none is recorded yet. SKIP later packages (add-python-package). SKIP scaffolding src/ (setup-workspace). HOW TO USE: detect, ask managed vs user-managed, ask the manager when needed, then env init, env sync, add Skore, and env verify. When setup-ml-project dispatched this turn, skip each ask whose answer is already recorded. One recorded answer does not skip the other ask.