code-explorer

name	code-explorer
description	Search and analyze code repositories on GitHub and Hugging Face (Models, Datasets, Spaces). This skill should be used when exploring open-source projects, finding implementation references, discovering ML models/datasets, or analyzing how others have solved similar problems.

Code Explorer

Overview

To search and analyze code repositories across GitHub and Hugging Face platforms, use this skill. It enables discovering implementation patterns, finding relevant ML models/datasets, and exploring demo applications (Spaces) for learning and reference.

Supported Platforms

Platform	Search Targets	Tool
GitHub	Repositories, Code	gh CLI
Hugging Face	Models, Datasets, Spaces	uvx hf CLI + huggingface_hub API

검색 품질 원칙 (필수)

1. 현재 날짜 확인

date +%Y-%m-%d

아래 예시의 연도는 참고용. 실제 검색 시 현재 연도 사용.

2. Long-tail Keywords 적용

예시의 Short-tail을 그대로 쓰지 말고 확장:

예시 (참고용)	실제 검색 (Long-tail)
"object detection"	"open vocabulary object detection pytorch inference {현재연도}"
"gradio demo"	"gradio image segmentation interactive demo huggingface"
"qwen vl"	"qwen2-vl vision language model zero-shot example code"

3. Multi-Query 적용

한 번에 찾기 어려우면 2-3개 관점으로 검색:

# 모델명 중심
gh search repos "qwen2-vl" --sort stars

# 기능 중심
gh search repos "vision language open vocabulary detection" --sort stars

# 구현 중심
gh search repos "vl model gradio demo inference" --sort stars

4. 필터 활용

# 최신 + 품질 필터 (현재 연도 적용)
gh search repos "keyword" stars:>50 pushed:>{현재연도-1}-01-01 --language python

5. 검색 전 체크리스트

• 현재 날짜 확인했는가?
• Short-tail을 Long-tail로 변환했는가?
• 필요시 2-3개 변형 쿼리로 검색했는가?
• 적절한 필터(언어, 스타, 날짜) 적용했는가?

---

Workflow Decision Tree

User wants to explore code/resources
    |
    +-- Looking for code implementations?
    |   +-- Use GitHub search
    |       +-- scripts/search_github.py (or gh CLI directly)
    |       +-- Analyze repo structure, README, key files
    |
    +-- Looking for ML resources?
        +-- Use Hugging Face search
            +-- scripts/search_huggingface.py (search via API)
            +-- uvx hf download (download files)

Scripts

Always run scripts with --help first to see usage. These scripts handle common search workflows reliably.

Available Scripts

• scripts/search_github.py - GitHub repository search using gh CLI
• scripts/search_huggingface.py - Hugging Face search (models, datasets, spaces)

Quick Examples

# GitHub search
python scripts/search_github.py "object detection" --limit 10 --help

# Hugging Face search
python scripts/search_huggingface.py "qwen vl" --type models --help

GitHub Search

Using gh CLI Directly

# Search repositories by keyword
gh search repos "open vocabulary detection" --sort stars --limit 10

# Filter by language
gh search repos "gradio app" --language python --limit 5

# View repository details
gh repo view owner/repo

# Search code within repositories
gh search code "Qwen2VL" --extension py

Repository Analysis

To analyze a found repository:

1. Review README.md for usage instructions
2. Identify main entry points (app.py, main.py, inference.py)
3. Check dependencies (requirements.txt, pyproject.toml)
4. Study implementation patterns in source files

Hugging Face Search

Search (via script or Python API)

# Search models
python scripts/search_huggingface.py "object detection" --type models --limit 10

# Search datasets
python scripts/search_huggingface.py "coco" --type datasets --limit 5

# Search spaces (demos)
python scripts/search_huggingface.py "gradio demo" --type spaces --limit 10

# Search all types
python scripts/search_huggingface.py "qwen vl" --type all

Download (via uvx hf)

# Download space source code (use /tmp/ for temporary analysis)
uvx hf download <space_id> --repo-type space --include "*.py" --local-dir /tmp/<space_name>

# Download model files
uvx hf download <repo_id> --include "*.json" --local-dir /tmp/<model_name>

# Download to project directory (when needed permanently)
uvx hf download <repo_id> --local-dir ./my-model

Note: Always use --local-dir /tmp/ for temporary code analysis to avoid cluttering the project.

Common Search Patterns

# Find models for specific task
python scripts/search_huggingface.py "open vocabulary detection" --type models
python scripts/search_huggingface.py "qwen2 vl" --type models
python scripts/search_huggingface.py "grounding dino" --type models

# Find demo applications
python scripts/search_huggingface.py "object detection demo" --type spaces
python scripts/search_huggingface.py "gradio image" --type spaces

Analyzing a Space

To understand how a Space is implemented:

1. Find the space: python scripts/search_huggingface.py "keyword" --type spaces
2. Download source: uvx hf download <space_id> --repo-type space --include "*.py" --include "requirements.txt" --local-dir /tmp/<space_name>
3. Or view online: https://huggingface.co/spaces/{space_id}/tree/main
4. Focus on app.py for main logic
5. Check requirements.txt for dependencies

Example Use Cases

Find Qwen3-VL Open Vocab Detection Code

# Search GitHub
gh search repos "qwen vl object detection" --sort stars
gh search code "Qwen2VL" --extension py

# Search Hugging Face
python scripts/search_huggingface.py "qwen2-vl" --type models
python scripts/search_huggingface.py "qwen vl" --type spaces

Find Gradio Demo Patterns

# Search spaces using Gradio
python scripts/search_huggingface.py "gradio object detection" --type spaces

# Download a space to study
uvx hf download username/space-name --repo-type space --include "*.py" --local-dir /tmp/space-name

Find Pre-trained Detection Models

python scripts/search_huggingface.py "object-detection" --type models --limit 20
python scripts/search_huggingface.py "grounding-dino" --type models
python scripts/search_huggingface.py "yolo-world" --type models

Resources

scripts/

• search_github.py - GitHub repository search wrapper
• search_huggingface.py - Hugging Face Hub search wrapper

references/

• github_api.md - GitHub CLI detailed reference
• huggingface_api.md - Hugging Face Hub API and CLI reference

Tips

1. Start broad, then narrow: Begin with general keywords, then add filters
2. Check stars/likes: Higher counts often indicate quality
3. Review recent activity: Recently updated repos are better maintained
4. Use --help first: Scripts have detailed usage information
5. Download selectively: Use uvx hf download --include to download only needed files
6. Always cite sources: Include repository URLs, Space links, or model IDs you referenced