GoldenJupyterDir Notebook Skill
SkillDev toolsLets your agent test the golden_jupyter_dir golden build.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the GoldenJupyterDir Notebook Skill skill
About this capability
Use when testing the golden_jupyter_dir golden build
What this skill tells your AI
The instructions your AI receives, as published by yusufkaraaslan/skill_seekers in tests/golden/phase2/jupyter_dir/SKILL.md and read by ahel’s review.
Use when testing the golden_jupyter_dir golden build
📋 Notebook Information
Kernel: Python 3
Language: python 3.11.4
💡 When to Use This Skill
Use this skill when you need to:
- Understand golden_jupyter_dir concepts and analysis workflow
- Reference code examples and their outputs
- Reproduce data analysis or computation steps
- Review methodology, visualizations, and results
- Find library usage patterns and best practices
📖 Section Overview
Total Sections: 5
Content Breakdown:
- Data Loading: 1 sections
- Evaluation: 1 sections
- Setup: 1 sections
- Other: 2 sections
🔑 Key Concepts
Main topics covered in this notebook
Major Topics:
- Getting Started
Subtopics:
- Modeling Results
📦 Dependencies
3 package(s) imported
numpypandassklearn
⚡ Quick Reference
Common documentation patterns found:
Getting Started (1 sections):
- Getting Started (section 1)
Modeling (1 sections):
- Modeling Results (section 5)
📝 Code Examples
High-quality code cells from notebook
Bash Examples (1)
Example 1 (Quality: 5.0/10):
pip install pandas
Python Examples (3)
Example 1 (Quality: 9.5/10):
def long_example():
x0 = 0
x1 = 1
x2 = 2
x3 = 3
x4 = 4
x5 = 5
x6 = 6
x7 = 7
x8 = 8
x9 = 9
x10 = 10
x11 = 11
x12 = 12
x13 = 13
x14 = 14
x15 = 15
x16 = 16
x17 = 17
x18 = 18
x19 = 19
x20 = 20
x21 = 21
x22 = 22
x23 = 23
x24 = 24
x25 = 25
x26 = 26
x27 = 27
x28 = 28
x29 = 29
x30 = 30
x31 = 31
x32 = 32
x33 = 33
x34 = 34
x35 = 35
x36 = 36
x37 = 37
x3
...
In [2] (Quality: 7.5/10):
import pandas as pd
df = pd.read_csv('data.csv')
df.head()
Example 3 (Quality: 2.0/10):
%timeit broken()
📊 Notebook Statistics
- Total Sections: 5
- Code Cells: 2
- Markdown Cells: 2
- Raw Cells: 1
- Notebooks: 1
- Programming Languages: 2
Language Breakdown:
- python: 3 code cells
- bash: 1 code cells
🗺️ Navigation
Reference Files:
references/section_s2-s2.md- Data Loadingreferences/section_s5-s5.md- Evaluationreferences/section_s1-s1.md- Setupreferences/section_s3-s4.md- Other
See references/index.md for complete notebook structure.
Generated by Skill Seeker | Jupyter Notebook Scraper
Signals
- GitHub stars
- 15k
- Forks
- 2k
- Last commit
- Sep 2026
ahel review
K1binfo
installs-packagesK1binfo
installs-packages (in references/section_s1-s1.md)
Automated review, not a security audit. Ruleset v1+k2.
Others that do the same job
Advanced
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golden-jupyter-dir- Source
- github.com/yusufkaraaslan/skill_seekers