Skip to content

[GitHub Trending] chopratejas/headroom

8.3 relevance
Score Breakdown
technical depth
8
novelty
9
actionability
9
community
8
strategic
6
personal
9

Scored daily by a customisable AI persona to surface the most relevant engineering leadership news.

Novel tool to compress LLM inputs, highly actionable and relevant to AI workflows.

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 (chopratejas/headroom) compresses AI agent inputs—tool outputs, logs, RAG chunks—by 60-95% using algorithms like SmartCrusher, CodeCompressor, and Kompress-base, while preserving accuracy on GSM8K, TruthfulQA, SQuAD, and BFCL benchmarks. It runs locally as a library (Python/TypeScript), proxy, agent wrapper (Claude Code, Codex, Cursor), or MCP server, with reversible CCR storage and cross-agent memory via headroom learn. CacheAligner stabilizes prefixes for provider KV cache hits, and the tool supports zero-code proxy mode and inline compression.

Author

chopratejas