Execute Jupyter notebooks using local scripts or MCP Jupyter. Arguments: <notebook_path> [--mode] [--cells] [--timeout] [--batch] [--save]
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See how to installReview the instructions the agent will receive before you install.
Execute a Jupyter notebook with full lifecycle management.
Notebook: $ARGUMENTS
--mode: full (default), selective, papermill--cells: Specific cells (e.g., 0,5,10)--timeout: Per-cell timeout in seconds (default 300)--stop-on-error: Halt on first error--batch: Enable BATCH_MODE for interactive notebooks--save: Save outputs to original notebookLocal scripts (preferred for batch):
# Full execution via notebook_tools.py
python scripts/notebook_tools/notebook_tools.py execute {path} --timeout 300
# Cell-by-cell with verbose output via notebook_helpers.py
python scripts/notebook_tools/notebook_helpers.py execute {path} --verbose
# Specific cell execution
python scripts/notebook_tools/notebook_helpers.py execute {path} --cell 5 --timeout 60
MCP (for interactive debugging):
manage_kernel(action="start", kernel_name="python3") + execute_on_kernelSetCurrentDirectory()mcp-jupyter skill for detailed .NET patterns.env configuration first (use /validate-genai)--batch for notebooks with interactive widgetspython scripts/genai-stack/validate_notebooks.py| Error | Cause | Solution |
|---|---|---|
| Kernel timeout | .NET cold start | Retry (30-60s normal) |
| File not found | Wrong directory | SetCurrentDirectory() |
| ModuleNotFoundError | Missing dependency | pip install |
| API key missing | .env not configured | Check OPENAI_API_KEY etc. |
Report: notebook name, kernel, mode, total/executed/successful/error cells, timing, error details.
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Cycle 30 min du secrétaire vérificateur myia-po-2026:CoursIA-3. Atteste en tiers, du plus ancien au plus récent, les PRs ouvertes sans dossier valide (chaque READY, une fois lu et approuvé par ai-01, est mergé sans attendre son cycle), et fait circuler l'information sur workspace-CoursIA-3.
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Analyze a Slidev deck qualitatively — organ reports (structure, composition) + vision AI on rendered PNGs. Arguments: <deck_id> [--slides 1,5,10]
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Build or improve Jupyter notebooks iteratively with quality scoring. Arguments: <new|improve|fix> <path> [--topic] [--domain] [--level] [--quality] [--max-iter]
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Detect cell-ordering / enchainement problems in Jupyter notebooks (canonical-order slippage, misplaced or forgotten cells). Arguments: [target] [--severity HIGH|MED|LOW] [--json]
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Clean up and reorganize markdown in enriched Jupyter notebooks. Arguments: [target] [--dry-run] [--aggressive] [--hierarchy-only]
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Cycle de coordination ai-01 (coordinateur UNIQUEMENT — jamais sur un worker). Lit memoire + dashboards + inbox + GitHub, merge les PRs pretes, tranche les design-gates, dispatche des grains par lane, reporte. Arguments: [--dispatch] [--focus <topic>]
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