ContextForge.
Open source CLI tool that scans your codebase, calculates relevance, and builds token-efficient context bundles for AI coding assistants. Runs 100% locally with zero external API keys.
The Friction with LLM Context
Developers frequently struggle with three major inefficiencies during AI coding sessions:
Digging through hundreds of files, guessing relevance, and copy-pasting code manually into chat boxes.
Sending entire function bodies and boilerplate that blows token limits and causes prompt degradation.
Models hallucinating across multi-file boundaries due to unstructured context payloads.
Digging through hundreds of files, guessing relevance, and copy-pasting code manually into chat boxes.
Sending entire function bodies and boilerplate that blows token limits and causes prompt degradation.
Models hallucinating across multi-file boundaries due to unstructured context payloads.
How ContextForge Works
ContextForge executes an intelligent 5-step local pipeline in milliseconds:
- Task Description: Parses your intent written in plain natural language.
- Repository Indexer: Scans the directory with strict
.gitignoreand lockfile exclusion. - Relevance Scoring: Evaluates symbol graphs and keyword proximity across source files.
- AST-Aware Compression: Extracts type contracts and function signatures while pruning implementation bodies.
- Clipboard Output: Copies a token-budgeted prompt ready for pasting into any LLM.
Installation & Usage
Coming Soon (In Active Beta)Upcoming global CLI distribution for local workflow integration: