probabl-ai/skills
14 skills
$npx skills add probabl-ai/skillsSkillInstalls
audit-ml-pipelineOwns the `audit/` folder: one `# %%` (jupytext percent) Python file per experiment, aligned 1:1 with `experiments/NN_<short_name>.py` and `journal/NN_<short_name>.md`, that loads the experiment's skorbuild-ml-pipelineDeclare the pipeline from data source to predictor as a **skrub DataOps graph** (not as a bare `sklearn.Pipeline`). Every step is either a pure-Python function (stateless) attached via `.skb.apply_fundata-science-python-stackOpinionated Python stack for data-science / ML work — one library per job, organized into tiers (mandatory / user choice / optional / transitive). SKILL.md is the index; per-library `references/<libraevaluate-ml-pipelineMethodology for evaluating a single sklearn-compatible learner (in particular, the `SkrubLearner` produced by `build-ml-pipeline`). Owns: which entry point to call (`skore.evaluate` first, the expliciexplore-ml-dataOwns data understanding BEFORE any model is designed. Places and executes `data/eda.py` (a jupytext `# %%` script) via the shared in-process runner, reads the streamed digest, then writes a persisted iterate-from-skoreSource the next ML experiment proposal by **reading the audit digest** at `scratch/audit/<stem>/audit.md` (produced by `audit-ml-pipeline` at § 4 record-outcome). For every row in the digest's `## Cheiterate-from-userSource the next ML experiment proposal from the user via one of three entry points selected by `AskUserQuestion`: (a) a scientific article URL the agent must read and synthesize, (b) a resource link oiterate-ml-experimentOwns the iteration loop on top of an ML workspace: the `journal/JOURNAL.md` index and the per-experiment `journal/NN_short_name.md` design notes that must be drafted and approved by the user **before*organize-ml-workspaceDecide 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/`, python-apiLook up the public API of a Python package against the *installed version* and cache what's worth keeping. Four shapes by question type: (0) cache hit under `scratch/api/<lib>/<version>/`; (1) `inspecpython-code-styleOwns Python code style for this stack: ruff for lint + format, numpydoc for docstrings. Three responsibilities — (1) place the project's `ruff.toml` from the bundled template once the stack and worksppython-env-managerSingle source of truth for "which Python environment manager does this project use, and how do I install a package with it?". Owns the detection table (pixi / uv / poetry / hatch / conda+mamba / pip+vsmoke-test-ml-pipelineOwns the smoke test contract for an ML experiment: a small, diagnostic-by-construction pytest that fits the experiment's learner on a portion of the real `data/` source and predicts on a *disjoint* potest-ml-pipelineOwns the `tests/` folder of an ML workspace and the pairing rule between an experiment and its tests. Lightweight router: every test category has its own subskill (`smoke-test-ml-pipeline` is the only