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Git-Mastery Exercises - AI Agent Guide

Repository Structure

40+ modular Git exercises with automated validation using pytest and git-autograder.

Exercise types:

  • Standard exercises (40+ directories): Complete with download.py, verify.py, test_verify.py, README.md, res/
  • Hands-on scripts (hands_on/): Single-file demonstrations without validation

Shared utilities (exercise_utils/): git.py, github_cli.py, cli.py, file.py, gitmastery.py, test.py

Available Skills

exercise-development: Creating exercises (standard vs hands-on)

  • References: exercise-utils, coding standards
  • Use for: implementing download.py, verify.py, test_verify.py, README.md

exercise-utils: Utility modules API reference

  • Standalone: git, github_cli, cli, file, gitmastery, test utilities
  • Never use raw subprocess calls

Quick Commands

./new.sh                      # Create exercise/hands-on (interactive)
./test.sh <exercise>          # Test one exercise
pytest . -s -vv               # Test all
ruff format . && ruff check . # Format & lint

Coding Standards

Style: 88 char lines, 4 spaces, double quotes, 2 blank lines between functions

Naming:

  • Functions/Variables: snake_case
  • Constants: UPPER_SNAKE_CASE
  • Classes: PascalCase
  • Directories: kebab-case

Type hints: Required on all function signatures

Imports: Order: stdlib, third-party, local (blank lines between)

Common mistakes:

  • Don't call git directly, use exercise_utils/git.py
  • Don't forget create_start_tag() at end of download.py
  • Don't hardcode paths, use Path(file).parent
  • Don't create tests without test_ prefix

Pre-commit: Run ruff format, ruff check, mypy, and ./test.sh

Contributing Workflow

  1. Create "exercise discussion" GitHub issue
  2. Wait for approval
  3. Use ./new.sh to scaffold
  4. Implement files
  5. Test thoroughly
  6. Submit PR referencing approved issue

Tech Stack

Python 3.13+, pytest, git-autograder 6.*, repo-smith, ruff, mypy, Git CLI, GitHub CLI (gh)