python-repo-quickstart — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited python-repo-quickstart (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Rapidly analyze and understand Python repositories to get started quickly.
When a user provides a Python repository:
Automated analysis:
python scripts/analyze_repo.py <repo_path>Manual analysis:
Check for framework indicators:
Django:
manage.py presentsettings.py in projectFlask:
app.py or application.pytemplates/ and static/ directoriesFastAPI:
main.py with app definitionuvicorn in dependenciesCLI Tool:
cli.py or __main__.pyargparse, click, or typer usageLibrary/Package:
src/ directory structuresetup.py or pyproject.tomlData Science:
.ipynb filesnotebooks/ directorySee: python-patterns.md for detailed patterns
Common entry points:
main.py - Standard entry pointapp.py / run.py - Web applicationmanage.py - Django managementcli.py - Command-line interface__main__.py - Package entry (python -m)Check for:
if __name__ == "__main__": blocksFind dependency files:
requirements.txt - Most commonrequirements-dev.txt - Development dependenciesPipfile - Pipenvpyproject.toml - Poetry or modern setupenvironment.yml - CondaExtract key dependencies:
Virtual environment:
# Standard venv
python -m venv venv
source venv/bin/activate # Linux/Mac
venv\Scripts\activate # WindowsInstallation:
# pip
pip install -r requirements.txt
# Development mode
pip install -e .
# Poetry
poetry install
# Pipenv
pipenv install
# Conda
conda env create -f environment.ymlConfiguration:
.env.example or .env.templateRunning:
# Direct execution
python main.py
# Module execution
python -m package_name
# Web frameworks
flask run
uvicorn main:app --reload
python manage.py runserver
# CLI tools
python cli.py --help
package-name --helpFrom README:
From code structure:
From dependencies:
Generate a quick start guide with:
Project: [Name]
Type: [Web App / CLI Tool / Library / Data Science / etc.]
Purpose: [Brief description]- Python [version]
- [Other system requirements]# 1. Clone repository (if needed)
git clone [url]
# 2. Create virtual environment
python -m venv venv
source venv/bin/activate
# 3. Install dependencies
pip install -r requirements.txt
# 4. Configure environment (if needed)
cp .env.example .env
# Edit .env with your settings
# 5. Run application
python main.py- main.py: Main application entry
- cli.py: Command-line interface
- tests/: Test suite- flask: Web framework
- sqlalchemy: Database ORM
- pytest: Testing framework- Feature 1: Description
- Feature 2: Description
- Feature 3: Descriptionpytest
# or
python -m pytest tests/- Configuration details
- Known issues
- Development tipsUser: "Analyze this Python repository" → Scan structure, identify type, generate quick start guide
User: "How do I run this project?" → Find entry points, dependencies, provide setup and run instructions
User: "What does this codebase do?" → Analyze README, code structure, dependencies to summarize functionality
User: "Help me understand this Python repo structure" → Explain directory organization, identify key components
User: "What are the prerequisites for this project?" → Identify Python version, system requirements, dependencies
User: "Generate setup instructions for this repo" → Create step-by-step installation and configuration guide
Use the provided script for quick automated analysis:
python scripts/analyze_repo.py /path/to/repoOutput includes:
Limitations:
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.