Solo developers on HN and r/programming repeatedly describe the same fear before touching legacy code: they don't know which files are 'cursed' — high churn, high bug history, zero tests — versus which are safe to modify. RefactorRisk connects to a GitHub repo, maps commit frequency against issue/PR bug tags over time, and produces a file-level risk heatmap with a prioritized 'touch this last' refactor sequence so solo devs can plan upgrades without accidentally detonating production.
Solo developers and small engineering teams maintaining 1-5 year old production codebases
Freemium — free for 1 public repo; $15/mo for private repos and team seats up to 3
Hacker News: The explosion of AI-assisted vibe-coded codebases means more solo developers are inheriting or maintaining code they didn't write, and the inherited-codebase dread thread is perennial on HN.
The explosion of AI-assisted vibe-coded codebases means more solo developers are inheriting or maintaining code they didn't write, and the inherited-codebase dread thread is perennial on HN.
GitHub OAuth login, repo selection, and a single heatmap page showing files ranked by commit frequency × linked bug count with a one-paragraph plain-English risk summary per top-10 file.
LLM reads commit messages and PR descriptions to classify changes as bug-fix vs. feature vs. refactor, making the churn signal far more accurate than raw commit count alone.
GitHub API rate limits and the need to parse issue/PR text for bug signals means false positives could erode trust; accuracy on messy repos is the core technical risk.
Likely buyers are engineering teams, platform leads, developer-experience teams, and technical founders. Start with Solo developers and small engineering teams maintaining 1-5 year old production codebases and look for teams already spending time or money on this workflow.
Find the first 10 users by searching for recent complaints around "developer tools refactoring" in Hacker News, developer communities, GitHub issues, and niche Slack or Discord groups. Offer a concierge version first: manually solve the workflow for a few users, then automate only the repeated steps.
Get a complete blueprint for building this app — tech stack, database schema, API endpoints, go-to-market plan, and more. Generated by AI in seconds. Download as Markdown.
To build a RefactorRisk: Code Churn vs. Bug Density Correlation Mapper for Solo Codebases app, start by validating the problem. Generate a full project spec above for a complete tech stack and build plan.
A medium difficulty app like this typically costs $0-$5,000 for an MVP. Monetization: Freemium — free for 1 public repo; $15/mo for private repos and team seats up to 3.
Solo developers and small engineering teams maintaining 1-5 year old production codebases