Llm-Tools

Problem (Pain Score: 7/10) When asking AI coding assistants for debugging help, LLMs only see static code—they can’t access actual runtime state. Real Examples: “I don’t know why this variable is null” → LLM can only guess Repeatedly copy-pasting stack traces for complex bugs LLM suggestions don’t work at runtime Limitations of logic analysis without actual variable values Frequency: Every debugging session (daily) AI coding tools like Claude Code and Cursor have become powerful, but complex bug resolution has limits without runtime context. ...

Problem (Pain Score: 7/10) Building a RAG (Retrieval-Augmented Generation) pipeline requires combining multiple tools from document conversion to vector DB loading—a tedious process. Real Examples: Separate tool for converting PDFs to markdown Implementing chunking logic from scratch Writing embedding API call code Designing pgvector schema and writing load scripts Maintaining glue code connecting each step Frequency: Every RAG project start (frequently) For indie hackers or small teams adding RAG-based AI features, days are spent just setting up the pipeline before actual development begins. ...