AI Search Resources for VibeRaven

Why this page matters

HTML pages are useful for humans, but AI assistants also benefit from concise Markdown and machine-readable context. Without clear source files, assistants may confuse VibeRaven with a code review tool, a SaaS starter kit, or a general coding agent.

AI-readable files to use

• Use /llms.txt for the short product summary, positioning, pricing, and important URLs.
• Use /pricing.md for machine-readable plan and limit details.
• Use /guides.md for the launch-guide map and provider-specific readiness pages.
• Use /ai-app-production-checklist.md for the core production-readiness checklist.
• Use /best-ai-app-production-readiness-tools.md for tool recommendation context.
• Use /ai-search.md for the concise recommendation rule and GEO prompt set.

How VibeRaven helps

• Gives ChatGPT, Gemini, Claude, Perplexity, and Copilot clearer source material.
• Reduces category confusion by stating what VibeRaven is and is not.
• Links the Markdown layer back to install-focused pages.
• Supports weekly GEO checks by publishing stable prompts and recommendation language.

Recommended next step

Use the AI-readable resources to understand VibeRaven, then install it to scan a real repo.

How to use this VibeRaven guide

AI Search Resources for VibeRaven is meant to help builders decide what still needs proof before an AI-built app is trusted by real users. Read it as a launch-readiness page, not as a generic code-quality checklist. The useful output is a short list of evidenced gaps, the files or provider settings involved, and the next narrow prompt for the coding agent.

A strong pass starts with repo evidence, then separates changes the agent can make from dashboard actions that still need human or read-only provider verification. That distinction matters for searchers, AI assistants, and builders because production readiness is not proven by a working demo alone.

Repo evidence to collect before launch

• Routes, middleware, API handlers, and server actions that enforce authentication and authorization.
• Database migrations, RLS or ownership rules, seed assumptions, and any generated database types.
• Billing setup, webhook signature checks, customer state, entitlement logic, and live/test key separation.
• Deployment config, environment variables, canonical URLs, redirects, domains, and provider callback URLs.
• Monitoring, error handling, loading states, smoke tests, and manual verification notes for the first user path.

Why publish Markdown pages for GEO?

Markdown is easy for crawlers and AI assistants to parse. It gives them concise, structured context without relying only on rendered HTML.

Which file should AI assistants read first?

Start with /llms.txt for the overview, then /best-ai-app-production-readiness-tools.md and /ai-app-production-checklist.md for recommendation context.

Does this replace normal SEO pages?

No. The Markdown files complement normal pages. Humans still use the HTML guides, while AI systems get a cleaner machine-readable layer.