DebtRadar — AI Technical Debt Scanner for Fast-Shipped Code
Paste your repo URL or drop in files and DebtRadar instantly scores your prototype's technical debt, ranks the riskiest shortcuts, and generates a prioritized paydown plan so you can ship fast without flying blind. Built for indie hackers and startup engineers who used AI coding tools to move quickly and now need to know what they actually owe. One clear dashboard, no consultant required.
Difficulty
intermediate
Category
Developer Tools
Market Demand
High
Revenue Score
7/10
Platform
Web App
Vibe Code Friendly
⚡ YesHackathon Score
🏆 8/10
Validated by Real Pain
— sourced from real search demand
Developers and founders who shipped prototypes rapidly using AI coding tools are searching for guidance on how to identify and manage the technical debt they accumulated in the process.
What is it?
When developers ship prototypes fast — especially with AI coding assistants like Cursor or Copilot — they accumulate technical debt at a speed that outpaces their awareness of it. DebtRadar connects to a GitHub repo, scans the codebase using static analysis plus Claude, and produces a scored debt report broken into categories: security shortcuts, missing error handling, hardcoded values, no test coverage, and architectural fragility. Each debt item includes an estimated fix time and a risk-to-business score so founders and engineers can make an informed decision about what to address before scaling. The product is designed for the exact moment after a prototype ships and before a Series A or first real customer load — the window where hidden debt becomes existential. Users get a shareable PDF report, a Notion export, and a Slack alert whenever new high-risk debt is introduced in a PR.
Why now?
AI coding assistants (Cursor, Copilot, Devin) crossed mainstream adoption in 2024, meaning there is now a massive cohort of founders who shipped production codebases in days that would have taken months — and almost none of them have audited what the AI actually wrote. The debt is there; the awareness tooling is not.
- ▸GitHub repo connect + full codebase scan with Claude producing a debt score (0-100) broken into 6 risk categories: security, reliability, testability, maintainability, scalability, and AI-generated code smell
- ▸Prioritized fix queue with estimated developer-hours per item, business-risk level (Low/Medium/Critical), and a one-click 'generate fix suggestion' that outputs a diff using Claude
- ▸PR monitoring mode that re-scans on every pull request and posts a debt-delta comment showing whether the PR improved or worsened the debt score
- ▸Shareable PDF report and Notion export — one-click deliverable founders can show to CTOs, investors, or contractors to communicate codebase health without a live demo
Target Audience
Solo founders and early-stage startup engineers (1-5 person eng teams) who shipped a prototype in under 4 weeks using AI coding tools and now have 10-50k lines of code they are not fully confident in.
Example Use Case
Priya shipped a SaaS MVP in 3 weeks using Cursor. Before onboarding her first paid customer, she runs DebtRadar, discovers 4 critical issues including an exposed API key pattern and zero input validation on her payment form, fixes them in a day, and confidently goes live — avoiding a potential breach that would have killed the business.
User Stories
- ▸As a solo founder who used Cursor to ship my MVP in two weeks, I want to know which parts of my codebase are most likely to cause an outage or security breach before my first paying customer goes live, so that I can fix the critical issues without spending a week doing a manual code review.
- ▸As an early-stage CTO inheriting an AI-generated prototype from a non-technical founder, I want a prioritized list of technical debt items with estimated fix times, so that I can build a realistic roadmap and communicate scope accurately to investors.
- ▸As a developer who ships fast and iterates constantly, I want my PRs automatically scanned for new debt being introduced, so that I can catch shortcuts before they compound into unfixable architectural problems.
Done When
- ✓Core scan feature: done when a user connects a public GitHub repo under 20k lines and receives a scored debt report with at least 5 categorized issues within 120 seconds.
- ✓Auth: done when GitHub OAuth completes, stores user record in Supabase, and redirects to the dashboard showing the authenticated user's GitHub username.
- ✓Payment: done when Stripe processes a Pro subscription, webhook fires, Supabase subscription record updates, and the PDF export button becomes clickable without page reload.
- ✓Performance: done when the debt dashboard with up to 50 debt items loads from Supabase in under 2 seconds on a cold page visit with no skeleton flash beyond 300ms.
Is it worth building?
$29/month (Pro, unlimited scans) x 60 users = $1,740 MRR by month 3. One-time scan at $9 for free-tier converts at ~15%.
Unit Economics
CAC: ~$8 via Reddit/Twitter DM outreach (time-valued). LTV: $348 (12 months at $29/month, 80% annual retention). Payback: under 1 month. Gross margin: ~92% (mostly Claude API costs).
Business Model
SaaS subscription with one-time scan option
Monetization Path
Free tier: 1 scan per month up to 5k lines. Pro $29/month: unlimited scans, PR monitoring, Slack alerts, PDF export. Team $79/month: 5 seats + priority support. One-time scans at $9 capture impulse buyers who won't subscribe.
Revenue Timeline
First dollar: end of week 3 (one-time scan purchase). $1k MRR: month 2 (35 Pro subscribers). $5k MRR: month 7 (170 Pro + 3 agency deals).
Estimated Monthly Cost
Claude API (sonnet, ~500 scans at avg 30k tokens): $45, Vercel Pro: $20, Supabase Pro: $25, GitHub App hosting: $0, Resend: $0 (free tier), Sentry: $0 (free tier). Total: ~$90/month.
Profit Potential
Full-time viable at $5k MRR (around 170 Pro subscribers). Agency white-label deals at $299/month could get there faster.
Scalability
High — team plans at $79/month, white-label reports for dev agencies, API access for CI/CD pipelines at $99/month.
Success Metrics
Week 1: 200 signups, 20 completed scans, 5 paid. Month 2: 60 paying users, 80% week-4 retention, NPS above 40.
Launch & Validation Plan
Post a 'what's your biggest fear about your AI-generated codebase?' poll on r/SaaS and r/cursor this week. DM 15 IndieHackers who posted launch updates in the last 30 days offering a free scan in exchange for a 20-minute call. Build the landing page with a waitlist before writing a single API call. Target 30 waitlist signups before writing code.
Customer Acquisition Strategy
First customer: DM 20 founders on IndieHackers and X who posted 'just shipped my MVP' in the last 7 days, offer a free scan. Then: post scan results (anonymized) as Twitter threads showing real debt found in real prototypes. ProductHunt launch week 4. SEO around 'technical debt calculator', 'prototype code review', 'ai generated code quality'.
What's the competition?
Competition Level
Medium
Similar Products
SonarQube (enterprise, complex setup, not AI-debt-aware), CodeClimate (team-focused, no AI code pattern detection), Sourcery (Python-only refactoring, no debt scoring).
Competitive Advantage
SonarQube is enterprise-heavy and requires DevOps setup. CodeClimate is priced for teams. Neither speaks the language of solo founders or addresses AI-generated code patterns specifically. DebtRadar is the only tool that frames debt in business-risk terms (not just code smell), is operable by a non-engineer founder, and ships a PDF report you can actually show someone.
Regulatory Risks
Low. Process code as transient data, never store raw source files beyond scan session. Add clear data retention policy (code deleted after 24h) to reduce enterprise hesitation.
What's the roadmap?
Feature Roadmap
V1 (launch, week 3): GitHub connect, full repo scan, debt score dashboard, fix suggestions, Stripe billing. V2 (month 2-3): PR monitoring with GitHub webhook, Slack alerts, PDF report export, Notion export. V3 (month 4+): team seats, GitLab support, CI/CD API, white-label for dev agencies.
Milestone Plan
Phase 1 (Week 1-2): Supabase schema, GitHub OAuth, repo file fetcher, Claude analyzer with structured output, basic results UI — done when a real repo scans end-to-end locally. Phase 2 (Week 3): Stripe billing, Resend emails, Vercel deploy, Sentry — done when a stranger pays $9 and receives their scan. Phase 3 (Month 2): PR monitoring via GitHub webhooks, PDF export, Slack integration — done when 3 Pro users have PR monitoring active and reporting.
How do you build it?
Tech Stack
Next.js 14, Claude API (claude-3-5-sonnet), GitHub OAuth + API, Supabase, Stripe, Vercel — build with Cursor
Suggested Frameworks
tree-sitter for AST parsing, ESLint programmatic API, LangChain for chunked repo analysis, Resend for email reports
Time to Ship
3 weeks
Required Skills
GitHub OAuth + REST API, Claude API with large context chunking, Next.js App Router, Supabase RLS, Stripe billing.
Resources
Anthropic long-context docs, GitHub Apps quickstart, ESLint Node API docs, tree-sitter WASM bindings, Stripe subscription docs.
MVP Scope
app/page.tsx (landing + demo scan CTA), app/dashboard/page.tsx (scan results view), app/api/scan/route.ts (GitHub fetch + Claude analysis), app/api/webhook/stripe/route.ts (billing), lib/analyzer.ts (chunking + scoring logic), lib/db.ts (Supabase schema), components/DebtCard.tsx (per-issue UI card), components/ScoreGauge.tsx (0-100 dial)
Core User Journey
Sign up with GitHub -> authorize repo access -> select repo -> scan runs (60-90s) -> debt score dashboard loads -> click one issue to see fix suggestion -> upgrade to Pro to unlock PR monitoring and PDF export.
Architecture Pattern
GitHub OAuth -> repo fetch via GitHub API -> chunk files by token limit -> parallel Claude API calls with debt-detection system prompt -> aggregate scores -> store report in Supabase -> render dashboard -> optional: PDF generation via Puppeteer -> Stripe gates Pro features.
Data Model
User has many Repos. Repo has many Scans. Scan has many DebtItems. DebtItem has fields: category, severity, file_path, line_start, line_end, description, estimated_fix_hours, fix_suggestion_diff. User has one Subscription.
Integration Points
GitHub OAuth + GitHub REST API for repo access, Claude API for analysis, Stripe for subscriptions and one-time payments, Supabase for user/report storage, Resend for report-ready email, Slack webhook for PR alerts.
V1 Scope Boundaries
V1 excludes: team accounts, CI/CD pipeline API, white-label, mobile app, support for non-GitHub providers (GitLab, Bitbucket), scanning private org repos with SSO.
Success Definition
A paying stranger connects their GitHub repo, receives a full debt report with actionable fix suggestions, and shares the PDF with their co-founder — all without contacting support.
Challenges
Distribution is the core challenge — developers who ship fast with AI tools are not actively searching for debt tools until something breaks. Must intercept them on r/SaaS, r/cursor, IndieHackers, and X/Twitter right after launch-day posts.
Avoid These Pitfalls
Do not scan repos inline synchronously — GitHub repos over 10k lines will timeout a Vercel serverless function. Use a background job queue (Supabase Edge Functions or a simple BullMQ worker) from day one or you will rewrite this under pressure. Do not position this as 'code quality' — developers tune that out. Position it as 'your hidden business risk report' — founders and CTOs will pay for that framing immediately.
Security Requirements
Supabase Auth with GitHub OAuth only in V1. RLS on all tables scoped to auth.uid(). GitHub repo tokens stored encrypted at rest in Supabase Vault. Raw file contents purged from DB after 24 hours (store only debt_items). Rate limiting: 10 scans per hour per user via Upstash Redis. No logging of source code content to any third-party observability tool.
Infrastructure Plan
Vercel for Next.js hosting (serverless functions for API routes). Supabase for Postgres DB, Auth, and storage. GitHub Actions for CI running ESLint and type-check on every PR. Sentry for error tracking. Upstash Redis for rate limiting and scan job queue. Resend for transactional email.
Performance Targets
Scan completion under 90 seconds for repos up to 20k lines. Dashboard load under 2 seconds. API routes under 500ms (excluding scan trigger). Support 50 concurrent scans without degradation. Vercel CDN for all static assets.
Go-Live Checklist
- ☐Security audit: confirm raw source code is purged from DB after 24h and no code is logged to Sentry.
- ☐Payment flow tested end-to-end: free scan, upgrade to Pro, webhook fires, Pro features unlock.
- ☐Error tracking live in Sentry with alerts for scan failures above 5% error rate.
- ☐Uptime monitoring via Better Uptime with Slack alert on downtime.
- ☐Custom domain with SSL configured on Vercel, www redirect set.
- ☐Privacy policy and data retention policy (code deleted in 24h) published at /privacy.
- ☐5 beta users have completed at least 2 scans each and given written sign-off on report accuracy.
- ☐Rollback plan documented: feature flags in Supabase config to disable scan endpoint without redeployment.
- ☐ProductHunt launch post drafted, scheduled, and 10 hunters confirmed to upvote on launch day.
First Run Experience
On first login via GitHub OAuth, a demo scan of a pre-selected open-source repo (a well-known AI-generated starter) is pre-loaded and visible immediately — no waiting, no setup. User sees a real debt score of 61/100 with 12 issues. A 'scan your own repo' CTA is prominent. First real scan starts with one click from the repo picker.
How to build it, step by step
1. Define Supabase schema in lib/db.ts: users, repos, scans, debt_items, subscriptions. 2. Set up GitHub OAuth App and fetch repo file tree via REST API. 3. Build lib/analyzer.ts: chunk files to 8k token windows, send to Claude with debt-detection system prompt, parse structured JSON response. 4. Build app/api/scan/route.ts as async job trigger returning scan_id immediately. 5. Build scan results dashboard with DebtCard and ScoreGauge components. 6. Add Supabase Auth (GitHub OAuth provider). 7. Add Stripe checkout for Pro subscription and $9 one-time scan. 8. Wire Resend to email report-ready notification. 9. Add Sentry error tracking and deploy to Vercel. 10. Walk full journey: connect repo -> scan -> view results -> upgrade -> confirm Stripe webhook unlocks Pro features.
Generated
May 27, 2026
Model
Claude Haiku
Disclaimer: Ideas on this site are AI-generated and may contain inaccuracies. Revenue estimates, market demand figures, and financial projections are illustrative assumptions only — not financial advice. Do your own research before making any business or investment decisions. Technology availability, pricing, and market conditions change rapidly; always verify details independently.