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Hey HN, I built geo-lint — an open-source linter for content (Markdown/MDX) that checks 92 deterministic rules across SEO, GEO (Generative Engine Optimization), content quality, and technical issues.

GEO is the idea that AI search engines (ChatGPT, Perplexity, Claude) cite content differently than Google ranks it. Things like question-formatted headings, FAQ sections, entity density, E-E-A-T signals, and citation-ready statistics all matter for whether an LLM will pull from your content. geo-lint has 35 rules specifically for this.

The interesting part is the lint loop. It ships as a Claude Code skill — you run /geo-lint audit and it spawns parallel subagents, one per file. Each agent reads the violations, edits the content, re-lints, and repeats until clean (max 5 passes). The linter is fully deterministic (no LLM in the rules themselves), so the agent gets unambiguous violation + suggestion pairs to act on. Zero hallucination risk in the analysis layer.

It also works without Claude Code — npx geo-lint --format=json gives you a flat JSON array any agent (Cursor, Copilot, Windsurf) can consume. The rules are the same either way.

MIT licensed, zero runtime deps beyond gray-matter. npm: @ijonis/geo-lint

GitHub: https://github.com/IJONIS/geo-lint

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