Lint-as-a-service for AI-generated code quality

What to build

A hosted linting/CI service built on Oxlint's AI-slop rule set (unsafe types, duplicate logic, low-value tests) that runs as a GitHub app or pre-commit hook, specifically marketed to solo developers and small teams shipping AI-generated TypeScript code.

Deslop proved there's a nameable problem — 'AI slop' in generated code — and a lightweight open-source fix; the opportunity is wrapping that same rule set into a paid, zero-config CI/GitHub app so teams don't have to self-host or maintain the linter config themselves.

Demand

Developers who rely on AI coding agents (Cursor, Copilot, Claude Code users) want a fast, specific signal that their agent-generated code is safe to merge, and a 27-point/6-comment Show HN response suggests the pain is recognized even if the audience is still small.

• Hacker NewsShow hn

  Show HN: Deslop – Oxlint rules for AI-generated TypeScript — 27 points, 6 comments on HN. Catches unsafe types, duplicate code, and low-value tests.

Stack

• Oxlint (rule engine base)
• GitHub Apps API
• TypeScript Compiler API / ts-morph
• Husky or Lefthook for pre-commit
• Stripe for subscription billing
• Vercel or Fly.io for hosting

Solo + AI difficulty

The linting rules themselves already exist as open source (Deslop), so the hard engineering is building a reliable GitHub App (PR checks, config UI, billing) rather than the detection logic itself; false-positive tuning and onboarding flow are the trickiest parts. A solo builder could ship a working GitHub App + Stripe paywall MVP in 2-4 weeks by wrapping the existing rules rather than writing new ones.

Entry threshold

Low barrier: the open-source rule set already exists as a base, so a solo builder can wrap it into a CI integration, dashboard, and subscription billing within a couple of weeks; main effort is packaging and multi-language rule coverage, not core tech.

Window

6-12 months

Where to find first users

• Hacker News (follow-up post on the hosted/CI version)
• GitHub Marketplace listing
• r/ExperiencedDevs and r/programming threads on AI code quality
• Indie Hackers and Product Hunt launch

Competitors

• CodeRabbit
• Qlty
• SonarQube

Counter-signals & risks

• Oxlint or other general-purpose linters may absorb similar AI-slop detection rules natively, eroding the differentiation of a standalone paid product.

• Detecting 'AI-generated' code smell is heuristic and prone to false positives, which could undermine trust and adoption of a paid service built on this premise.

• Monetization is uncertain: open-source linting tools often struggle to convert a Show HN audience into paying CI/pre-commit subscribers, especially against free alternatives like ESLint and Oxlint itself.