analytic-workbenchlisted

Use this skill for analytics and data-science workflow setup, exploratory analysis, notebook-first EDA, repo normalization for analysis projects, experiment comparison, AutoML, causal analysis, and promotion from ad hoc exploration into reusable pipelines. Trigger when the user asks for analysis best practices, how to structure an analytics repo, how to organize notebooks and runs, whether to use marimo or Quarto/qmd, how to handle experiment sweeps, how to compare models, or how to make analysis reproducible. Also trigger on phrases such as analytic workbench, EDA, exploratory analysis, notebook workflow, analytics pipeline, reproducible analysis, experiment sweep, hyperparameter comparison, comparison table, marimo, Quarto, qmd, Hamilton, sf-hamilton, dataflow, DAG driver, Hydra, DVC, Kedro, MLflow, AutoML, PyCaret, causal analysis, feature engineering, or model review.
bayeslearner/bayeslearner-skills · ★ 0 · AI & Automation · score 65

Install: claude install-skill bayeslearner/bayeslearner-skills

# Analytic Workbench Human-directed, AI-operated analysis. The AI computes; the human steers through a review surface (marimo notebook or Quarto doc). This is not a batch pipeline — intermediate findings are presented for redirection at every step. ## Start Here 1. Read `AGENTS.md` or `agents.md` if present 2. If neither exists, create `AGENTS.md` and update `CLAUDE.md` (see below) 3. Inspect the repo before changing structure 4. Separate repo facts from agent assumptions 5. Separate frozen inputs from live pulls Then establish per area: current mode, likely next mode, **review surface**, first boundary-sensitive change. ### Fresh Repo Bootstrap When starting on a repo with no `AGENTS.md`, create one from the initial prompt and project context. The file anchors all agents to the same workflow contract. `AGENTS.md` should contain: - **Project purpose** — one-paragraph summary derived from the user's request - **Workflow** — state that this project uses the analytic workbench skill with modes `probe → explore → experiment → operate` - **Current mode** — the mode established in the first `plan` declaration - **Review surface** — marimo or qmd, chosen at first `plan` - **Conventions** — module layout (`src/<project>/analysis/`), artifact layout (`runs/`, `rawdata/`) - **Steering rules** — any project-specific constraints from the user's prompt (e.g., data sources, review expectations, domain context) Then ensure `CLAUDE.md` exists and includes a pointer: ```text S