Reverse engineer a complex codebase into business workflows, connected code, edge cases, and evidence-backed risks.
⭐ Hit Star to help increase UnvibeCode's visibility among developers.
Unvibe complex code. Trace what the business actually does.
Reading files one by one does not show the complete business workflow. Pasting a large repository into an LLM can also lose the connections between entry points, state changes, dependencies, edge cases, and business outcomes.
UnvibeCode reverse-engineers a complex codebase into business workflows, connected code, edge cases, and evidence-backed risks.
Requires Python 3.11 or newer.
py --version
py -m pip install --upgrade unvibecode
py -m unvibecode --help
py -m unvibecode review --repository "D:\path\to\repository"Example:
py -m unvibecode review --repository "D:\Projects\customer-support-agent"python3 --version
python3 -m pip install --upgrade unvibecode
python3 -m unvibecode --help
python3 -m unvibecode review --repository "/path/to/repository"Example:
python3 -m unvibecode review --repository "/Users/yourname/Projects/customer-support-agent"python3 --version
python3 -m pip install --upgrade unvibecode
python3 -m unvibecode --help
python3 -m unvibecode review --repository "/path/to/repository"Example:
python3 -m unvibecode review --repository "/home/yourname/projects/customer-support-agent"No activation key. No customer OpenAI API key. The repository path is the only required input.
UnvibeCode helps developers understand what a codebase does, how its components connect, and what could break — without manually tracing every file.
Reconstruct business workflows from source code. Explore execution paths, decisions, dependencies, state changes, and the implementation behind each workflow.
Useful for: onboarding, reverse engineering, understanding legacy applications, and exploring unfamiliar repositories.
Explore interactive relationships between source files, imports, symbols, and dependencies. Select a file, inspect its connections, and download focused code context for further investigation.
Useful for: debugging, dependency tracing, architecture exploration, and preparing connected code for AI assistants.
Identify potential business-impacting implementation defects supported by source evidence. Explore affected workflows, implementation behavior, potential impact, remediation, and verification checks.
Useful for: investigating business logic defects, reviewing AI-generated applications, and identifying fragile workflows.
Not every repository produces confirmed risk findings. UnvibeCode distinguishes supported findings from cases where evidence is insufficient.
Download a normalized repository ZIP for code review, documentation, or further AI-assisted investigation. Need less code? Use the Connected Code Map to retrieve a focused context package around a selected file.
Useful for: engineering handoffs, repository exploration, and reusable source context.
More source code doesn't automatically mean better code understanding.
“The workflow and code maps helped me quickly trace relationships between routes, services, models, and database-related code.”
Subhankar Nath
“The Business Risk Findings report caught a real bug I didn't know about: my meditation-save endpoint always inserts a new row, but the model has a unique constraint on user + date, so a repeat save on the same day throws an unhandled error.”
Rohit Sanju Patil
| Tool | Primary strength | UnvibeCode difference |
|---|---|---|
| Aider | AI-assisted code editing | Repository-wide workflow and risk investigation without an editing task |
| Repomix | Repository packaging for AI | Interactive code maps, business workflows, and evidence-backed risks |
| Qodo PR-Agent | Pull-request review | Understand existing application behavior beyond a proposed code change |
| CodeQL | Static security and correctness analysis | Business workflow explanations connected to implementation and operational consequences |
A clearer, easier-to-explore repository review experience.
- Review results at a glance: See available outputs, identified workflows, and supported business-risk summaries directly in the CLI.
- Explore results while analysis continues: Access the interim Connected Code Map before deeper business analysis finishes.
- Open reports directly: The CLI provides interim and final HTML report paths, with clickable links in supported terminals.
- Cleaner progress updates: Fewer repetitive messages and no intermediate elapsed-time estimates.
- More useful final summary: Find the generated outputs, key workflows, and full results location together.
Understanding an unfamiliar repository
Discover business workflows, connected components, and implementation paths without manually opening every file.
Reviewing AI-generated applications
Understand what was actually implemented and investigate potential business logic defects.
Debugging across multiple files
Trace dependencies and surrounding code before changing a function in isolation.
Investigating application risks
Review source-backed findings and understand potential operational consequences.
Preparing context for AI coding assistants
Download complete repository context or focused connected code for further investigation.
Connected-code mapping and context preparation recognize:
| Language | File types |
|---|---|
| Python | .py |
| JavaScript | .js, .jsx, .mjs, .cjs |
| TypeScript | .ts, .tsx |
| Rust | .rs |
| PHP | .php |
| Ruby | .rb |
| HTML and CSS | .html, .htm, .css |
Analysis depth varies by language and repository structure. See limitations for details.
- Quick Start
- Understanding the Four Outputs
- How UnvibeCode Works
- Limitations and Responsible Use
- Data Processing and Privacy
- Troubleshooting
- Public Repository Reviews
Contributions are welcome in documentation, testing, examples, and supported tooling.
Found a problem or have a feature request? Open a GitHub issue.
For product questions, repository reviews, or collaboration, contact divya.singaravelu@iiml.org.
See LICENSE for reuse and distribution terms.