Refines and improves AI prompts using workspace-aware context from your project's tech stack, structure, and dependencies. Includes tools to analyze prompt quality and generate well-structured prompts from raw ideas.
Context intelligence for AI coding sessions. 7 MCP tools to score, compare, compress, build, and scan prompts across 9 AI tools. Rule-based, <5ms/prompt, all analysis runs locally.
Static analysis for vibe-coded apps. Flags security, reliability, performance, and AI quality issues in code generated by Cursor, v0, Bolt, and Copilot.
AI development observability platform. It silently captures structured data from vibe coding sessions via MCP and codifies deviation patterns into project rules to make AI write better code. 100% local and zero runtime dependencies.
A code ingestion tool that transforms your code into AI-optimized prompts instantly. Gather the relevant context with code2prompt under the hood. Learn more at code2prompt.dev