Project Info

AI Radar

Devpost

Inspiration

Modern software teams work on large codebases with multiple developers contributing simultaneously. While implementing a feature, developers often don't realize that someone else has already modified the same file or that an active pull request is changing the same area. These issues are usually discovered only during code review or merge, resulting in merge conflicts, duplicated work, and unnecessary debugging. We wanted to solve this problem by giving developers engineering awareness before they start writing code. What It Does AI Radar is a VS Code extension that analyzes the currently opened file and provides engineering context in a single view. It helps developers understand: Recent file changes Why the file changed Related Pull Requests Active contributors Affected engineering areas Risk level Recommended tests Suggested next actions Instead of searching through Git history, GitHub, and documentation, developers get all the relevant information directly inside VS Code before making changes. How We Built It The extension is built using the VS Code Extension API and TypeScript. It combines multiple sources of engineering information: Local Git history Git Blame Git Status Repository analysis GitHub REST API (optional) AI-powered engineering recommendations The extension analyzes the active file, collects engineering signals, calculates a risk level, and presents everything through a custom VS Code WebView. Challenges We Faced The biggest challenge was bringing together information from multiple sources into a single, meaningful engineering view. Some of the challenges included: - Parsing Git history efficiently Github Ratelimits Balancing useful information without overwhelming the developer was another major challenge. What We Learned Throughout this project we gained experience with: VS Code Extension Development Git internals and repository analysis GitHub REST APIs Engineering workflow automation Building developer productivity tools Designing AI-assisted developer experiences Most importantly, we learned that preventing problems early is often more valuable than fixing them later. Future Plans We plan to extend AI Engineering Radar with: AI-generated engineering summaries Cross-file dependency analysis Database and API impact detection Branch conflict prediction Team collaboration insights Continuous background monitoring Marketplace release for VS Code Our vision is to make AI Engineering Radar an intelligent engineering companion that helps developers understand their codebase before they write code, reducing merge conflicts and improving collaboration across large development teams.

Analysis

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Metric

Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.

Technology

Found in codeClaimed only
  • TypeScriptIn code
  • CSSClaimed
  • HTMLClaimed
  • JavaScriptClaimed
  • Node.jsClaimed
  • OpenAIClaimed

1 of 6 appear in the indexed code. 5 claimed on Devpost could not be matched to code, which may simply mean the tool leaves no trace in the repository.

AI coding agents

No AI coding agent signals were found in this repository.

Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.

Codebase size

Source size

182 KB

Source files

39

Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.

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