pymc-labs

working-with-marimo

@pymc-labs/working-with-marimo
pymc-labs
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90 forks
Updated 1/18/2026
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Interactive development in marimo notebooks with validation loops. Use for creating/editing marimo notebooks and verifying execution.

Installation

$skills install @pymc-labs/working-with-marimo
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Details

Path.claude/skills/working-with-marimo/SKILL.md
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Scoped Name@pymc-labs/working-with-marimo

Usage

After installing, this skill will be available to your AI coding assistant.

Verify installation:

skills list

Skill Instructions


name: working-with-marimo description: Interactive development in marimo notebooks with validation loops. Use for creating/editing marimo notebooks and verifying execution.

Working with Marimo

Follows a Plan-Execute-Verify loop to ensure notebook correctness.

Feedback Loop

  1. Context & Plan:

    • Sessions: mcp_marimo_get_active_notebooks (Find session IDs).
    • Structure: mcp_marimo_get_lightweight_cell_map (See cell IDs/content).
    • Data State: mcp_marimo_get_tables_and_variables (Inspect DataFrames/Variables).
    • Cell Detail: mcp_marimo_get_cell_runtime_data (Code, errors, local vars).
  2. Execute:

    • Edit the .py file directly using write or search_replace.
    • Rule: Follow Best Practices (e.g., @app.cell, no global state).
  3. Verify (CRITICAL):

    • Lint: mcp_marimo_lint_notebook (Static analysis).
    • Runtime Errors: mcp_marimo_get_notebook_errors (Execution errors).
    • Outputs: mcp_marimo_get_cell_outputs (Visuals/Console).

Common Commands

  • Start/Sync: Marimo automatically syncs file changes.
  • SQL: Use mo.sql for DuckDB queries.
  • Plots: Use plt.gca() or return figure. No plt.show().

Reference

See Best Practices for code formatting, reactivity rules, and UI element usage.