← ClaudeAtlas

repo-geolisted

Audit and optimize a code repository for AI/LLM discoverability (GEO). Use when the user asks to make a repo discoverable by AI, mentions GEO, llms.txt, AI visibility, "让 AI 搜到我的项目", "给这个仓库做 GEO", AI SEO for a project, or wants README/docs structured so ChatGPT, Claude, and Perplexity cite it accurately. Works on backend-only, frontend-only, and full-stack repos.
BazingaOrg/repo-geo · ★ 0 · AI & Automation · score 72
Install: claude install-skill BazingaOrg/repo-geo
# repo-geo Make a repository accurately findable and citable by AI search systems. Audit first, report, get confirmation, then edit. ## Core principle Every change must make it **easier for a model to accurately understand what already exists**. Never add content that restates information already on the page. If a proposed change does not add new information, drop it. Ranking tricks, padding, and score-chasing are out of scope and actively harmful. ## Workflow Run these phases in order. Do not skip to editing. ### Phase 1 — Detect repo type Inspect the repo root and classify into exactly one of: - **backend** — no site output. Signals: `pyproject.toml`, `go.mod`, `Cargo.toml`, `package.json` without a bundler/framework, presence of `openapi.*` / `main.go` / `src/lib`, absence of `index.html` / `public/`. - **fullstack** — both. Signals: `next.config.*`, `nuxt.config.*`, `remix.config.*`, or a `web/` + `server/` split, or `package.json` with both a server framework and a UI framework. - **frontend** — site or client app. Signals: `index.html`, `public/`, `dist/`, `vite.config.*`, static site generators (Hugo, Astro, Docusaurus, VitePress). State the classification and the evidence you used before continuing. If ambiguous, ask. Also determine: is there a **published site** (a domain this repo deploys to)? Site-level items only apply if yes. Read `references/repo-types.md` for the per-type action table. ### Phase 2 — Audit (read-only) Run the audit script: ```bash p