A cross-platform command-line tool for Git repository analysis. Profile commit history, detect code hotspots, generate diff reports, and optionally leverage AI for deeper insights. The generated git diff files integrate seamlessly with Cursor for collaborative development.
- Commit history analysis - browse and filter recent commits by time range, author, email, keyword, or commit hash
- Code hotspot detection - identify frequently modified files and directories to spot active areas
- Flexible search modes - union (match any condition) or intersection (match all conditions)
- Diff report generation - produce aggregated
.diffreport files for review in Cursor or other tools - AI-powered analysis - optional OpenAI / Azure OpenAI integration for automated commit summarization
- Interactive dashboard - Plotly Dash visualization via the
codet-dashcommand - JSON export - structured per-commit JSON output for downstream pipelines (
-oj) - Cross-platform - works on Windows, macOS, and Linux
pip install codetgit clone https://github.com/host452b/codet.git
cd codet
pip install -e .pip install -e ".[dev]"# analyze the current repo, last 7 days, with hotspot analysis
codet -d 7 -s
# search for keywords "Triton" and "cuda" in a cloned repo
git clone https://github.com/pytorch/pytorch.git
codet -d 7 -k Triton -k cuda -s -p pytorch
# filter by author email
codet -d 14 -e alice@example.com
# filter by commit hash (supports partial match)
codet -c abc1234
# intersection mode: must match ALL conditions
codet -d 7 -k feature -e dev@example.com -m intersectionusage: codet [-h] [--version] [-d DAYS] [-e EMAIL] [-u USER] [-k KEYWORD]
[-c COMMIT] [-g] [-r] [-p PATH] [-s] [-m {union,intersection}]
[-mo MODEL] [-to API_TOKEN] [-oe OPENAI_ENDPOINT]
[-cp CUSTOM_PROMPT] [-f INPUT_FILE] [-oj]
| Flag | Description | Default |
|---|---|---|
-d, --days |
Look back N days for commits | 30 |
-e, --email |
Filter by author email (repeatable) | — |
-u, --user |
Filter by author name (repeatable) | — |
-k, --keyword |
Search keyword in commit diffs (repeatable) | — |
-c, --commit |
Filter by commit hash, supports partial match (repeatable) | — |
-g, --debug |
Enable debug logging | False |
-r, --recursive |
Recursively scan subdirectories for git repos | True |
-p, --path |
Path to analyze | current directory |
-s, --hotspot |
Enable code hotspot analysis | True |
-m, --mode |
Search mode: union or intersection |
union |
Codet works with any OpenAI-compatible API — just pass the endpoint and model name:
| Flag | Description | Default |
|---|---|---|
-mo, --model |
Model name as required by your provider (e.g., gpt-4.1, openai/openai/gpt-5-nano, llama3) |
— |
-to, --api-token |
Bearer token (or set AI_API_TOKEN env var). If not set, AI analysis is skipped |
— |
-oe, --openai-endpoint |
Base URL of the API (/v1 is appended automatically if missing) |
— |
-cp, --custom-prompt |
Custom prompt appended to AI analysis | — |
-f, --input-file |
Additional file to include in AI analysis | — |
-oj, --output-cook-json |
Export per-commit JSON reports to json_cook/ |
False |
Examples with different providers:
# Standard OpenAI
codet -d 10 -s -to $OPENAI_KEY -oe "https://api.openai.com/v1" -mo "gpt-4.1"
# Local Ollama
codet -d 10 -s -to ollama -oe "http://localhost:11434/v1" -mo "llama3"Codet includes an interactive Plotly Dash dashboard for visualizing analysis results.
# launch dashboard with JSON data directory
codet-dash --json-path json_cook/Each run generates a git_patch_report_<timestamp>.diff file containing aggregated patches with contextual metadata. Open it directly in Cursor for AI-assisted code review.
With -oj, per-commit JSON files are written to json_cook/<repo_name>/, each containing commit metadata, changed files, and optional AI summaries.
git clone https://github.com/host452b/codet.git
cd codet
pip install -e ".[dev]"
# lint
flake8 . --max-line-length=127
# format
black .
isort .
# test
pytestMIT License. See LICENSE for details.