---

name: enrich-notebooks description: Enrich Jupyter notebooks with pedagogical markdown content. Arguments: [target] [--execute] [--fix-errors] [--strict] [--consecutive] [--iterate]

Enrich Notebooks

Add pedagogical markdown content to Jupyter notebooks.

Target: $ARGUMENTS

Arguments

• target: Notebook path, family name (Infer, Sudoku, Tweety, Lean, GenAI, etc.), or all
• --execute: Run notebooks and capture outputs before enriching
• --fix-errors: Correct code errors found during execution
• --strict: Require interpretation after EVERY code cell
• --consecutive: Focus on consecutive code cells without markdown
• --iterate: Use cell-iterator for iterative correction

Process

1. Parse target - Discover notebooks to enrich

2. For each notebook, launch a background agent:

   • Read the notebook-enricher agent instructions (.claude/agents/notebook-enricher.md)
   • Analyze structure: python scripts/notebook_tools/notebook_helpers.py list {path} --verbose
   • Find gaps programmatically (Python API):

     from scripts.notebook_helpers import NotebookHelper
     helper = NotebookHelper(path)
     gaps = helper.find_cells_needing_enrichment()      # Cells missing interpretation
     consecutive = helper.find_consecutive_code_cells()  # Code cells without markdown between
     

   • Validate placement: helper.validate_enrichment_context(cell_index) returns what's needed
   • Insert markdown cells via NotebookEdit (bottom-to-top to preserve indices)
   • Verify with: helper.get_cell_sequence(start, end) after each insertion

3. If --execute: Execute notebooks first to capture outputs for interpretation

4. If --fix-errors: Analyze errors, propose corrections, re-execute

5. If --consecutive: Prioritize fixing consecutive code cells

6. If --iterate: Use notebook-cell-iterator agent for targeted cell fixes

Agent Delegation

Use model: sonnet for enrichment agents (good balance of speed and quality). For complex domains (Probas, Lean), consider model: inherit for better reasoning.

Task(
    subagent_type="general-purpose",
    model="sonnet",
    prompt="Tu es un agent notebook-enricher. Lis .claude/agents/notebook-enricher.md. Enrichis: {path}",
    description=f"Enrich {name}",
    run_in_background=True
)

Enrichment Criteria

| Type | Placement | Tense | |------|-----------|-------| | Section intro | BEFORE code | Future: "This code will..." | | Code explanation | BETWEEN code cells | Present: "This function..." | | Result interpretation | AFTER code output | Past: "The results show..." | | Transition | Between sections | "After seeing X, let's explore Y..." | | Conclusion | End of section | Summary table |

After Enrichment

• Verify with git diff (expect more insertions than deletions)
• Run the enrich-quality scanner (rule C.7, mandatory):

  git show origin/main:<nb-path> > /tmp/base.ipynb
  python scripts/notebook_tools/scan_enrich_quality.py <nb-path> --base /tmp/base.ipynb
  # 0 HIGH finding before commit: anchors must resolve at HEAD (code[N] =
  # N-th CODE cell, 0-based, final layout), accents must survive, hrefs must
  # resolve, no phantom entities, no worked solution before a TODO exercise.
  

• Consider running /cleanup-notebooks to fix any positioning issues
• Update MEMORY.md with lessons learned about positioning accuracy