PromptAudit: LLM Cost Leak Detector
Analyzes your codebase to find expensive LLM API calls being made unnecessarily, helping AI-powered apps cut token spend by 30-50%.
The Problem
Developers building with AI tools like Cursor and Lovable are shipping apps with wasteful LLM patterns—redundant API calls, oversized prompts, missing caching—but have no visibility into which parts of their code are hemorrhaging tokens and dollars. They see high bills but can't pinpoint the source.
Target Audience
Solo/small team AI-native app builders using Claude, GPT, or Gemini APIs; particularly those on tight margins who've been surprised by $500+ monthly bills from poorly optimized implementations.
Why Now?
LLM API costs are now a primary concern for indie developers; Cursor/Lovable have removed friction to shipping AI apps, creating a cohort of cost-blind builders who need tools to scale sustainably.
What's Missing
LLM providers optimize for adoption, not cost awareness; generic dev tools don't understand token economics; there's a wedge for a specialized, actionable analyzer built by developers for developers.
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