Intelligently analyzes codebases to enhance LLM prompts with relevant context, featuring adaptive context management and task detection to produce higher quality AI responses.
Automatically generates and manages a prompts system for software projects, enabling persistent context for AI coding assistants through project scanning, requirement clarification, and module tracking.
Enables coding agents to access structured product context (decisions, goals, evidence) from meetings and tools, ensuring they build from actual product decisions.
An AI Context Engineer that transforms vague queries into structured context packages for LLMs by extracting code, mapping relationships, and providing insights.
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.
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