14-stage Fusion Pipeline for LLM token compression — reversible compression, AST-aware code analysis, intelligent content routing. Zero LLM inference cost. MIT licensed.

Drop-in prompt compression for production LLM apps. Cut your token bill 40-60% without changing your code. Python SDK, LLMLingua-2, MIT.

JavaScript/TypeScript implementation of LLMLingua-2 (Experimental)

A self-improving knowledge base about LLM agent infrastructure

Python command-line tool for interacting with AI models through the OpenRouter API/Cloudflare AI Gateway, or local self-hosted Ollama. Optionally support Microsoft LLMLingua prompt token compression

Lossless-first prompt compression for JSON, YAML, CSV, and Markdown. Library, CLI, MCP server, desktop app, and browser extension.

Rolling context compression for Claude Code — never hit the context wall. Auto-compresses old messages while keeping recent context verbatim. Zero config, zero latency. Works as a Claude Code plugin.

Reverse T9 for LLMs. Free, open-source prompt compressor for your AI prompts and agents.

CUTIA: compress prompts while preserving quality

A Claude Code skill that shrinks massive prompts and files using LLMLingua to save tokens.

A curated list of strategies, tools, papers, and resources for reducing LLM token costs and improving efficiency in production.

AI-assisted context management and prompt compression toolkit for developer productivity, ADR workflows, and LLM token optimization.

TOON for TYPO3 — a compact, human-readable, and token-efficient data format for AI prompts & LLM contexts. Perfect for ChatGPT, Gemini, Claude, Mistral, and OpenAI integrations (JSON ⇄ TOON).

This repository is the official implementation of Generative Context Distillation.

LLMLingua-2 prompt compression hook for Claude Code — cut token usage by ~55%

Advanced token reduction and prompt optimization framework for LLMs, featuring linguistic, algorithmic, and architectural patterns.

Compress LLM Prompts and save 80%+ on GPT-4 in Python

Enhance the performance and cost-efficiency of large-scale Retrieval Augmented Generation (RAG) applications. Learn to integrate vector search with traditional database operations and apply techniques like prefiltering, postfiltering, projection, and prompt compression.

PirateBao is a TypeScript/Bun agent-skill package for terse pirate-speak AI coding replies that preserve technical detail while cutting filler, with hooks, compressor CLI, OpenCode/Codex/Claude/Gemini cargo, .bao validation, npmjs gates, and token eval checks.

API gateway for LLM prompt compression with policy enforcement built on LLMLingua. Demonstrates cost control, prompt safety, and LLM execution boundaries.