openhands/jupyter
skills/jupyter/SKILL.md
Read, modify, execute, and convert Jupyter notebooks programmatically. Use when working with .ipynb files for data science workflows, including editing cells, clearing outputs, or converting to other formats.
$ install --global
skillsauthnpx skillsauth add openhands/skills jupyterInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 10, 2026, 9:22 AM10.1s2 files scanned
SKILL.md
- name:
- jupyter
- description:
- Read, modify, execute, and convert Jupyter notebooks programmatically. Use when working with .ipynb files for data science workflows, including editing cells, clearing outputs, or converting to other formats.
Jupyter Notebook Guide
Notebooks are JSON files. Cells are in nb['cells'], each has source (list of strings) and cell_type ('code', 'markdown', or 'raw').
Modifying Notebooks
import json
with open('notebook.ipynb') as f:
nb = json.load(f)
# Modify nb['cells'][i]['source'], then:
with open('notebook.ipynb', 'w') as f:
json.dump(nb, f, indent=1)
Executing & Converting
jupyter nbconvert --to notebook --execute --inplace notebook.ipynb # Execute in place
jupyter nbconvert --to html notebook.ipynb # Convert to HTML
jupyter nbconvert --to script notebook.ipynb # Convert to Python
jupyter nbconvert --to markdown notebook.ipynb # Convert to Markdown
Finding Code
grep -n "search_term" notebook.ipynb
Cell Structure
# Code cell
{"cell_type": "code", "execution_count": None, "metadata": {}, "outputs": [], "source": ["code\n"]}
# Markdown cell
{"cell_type": "markdown", "metadata": {}, "source": ["# Title\n"]}
Clear Outputs
for cell in nb['cells']:
if cell['cell_type'] == 'code':
cell['outputs'] = []
cell['execution_count'] = None
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