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[GitHub Trending] chopratejas/headroom

9.1 relevance
Score Breakdown
technical depth
8
novelty
8
actionability
8
community
8
strategic
7
personal
10

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New open-source tool for compressing LLM context, highly novel, actionable, and perfectly aligned.

AI/ML github.com
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 60-95% fewer tokens, same answers. Library, proxy, MCP server. - chopratejas/headroom
Summary

Headroom is an open-source context compression layer for AI agents that cuts token usage by 60–95% using six algorithms (JSON/AST/prose) and CacheAligner to stabilize KV cache prefixes. It integrates as a Python/TypeScript library, drop-in proxy, agent wrap (Claude Code, Codex, Cursor), or MCP server, with reversible CCR storage and cross-agent memory. Real-world savings include 92% on SRE debugging (65.7k→5.1k tokens) and 92% on code search, while preserving accuracy on GSM8K (0.87) and boosting TruthfulQA; the learning module mines failed sessions to write corrections to CLAUDE.md/AGENTS.md.

Author

chopratejas