llm-cost-reduction

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

An effective and efficient coding-agent setup in under 30 seconds: best tools, unified instructions, any OS.

Neural context compression for long-running AI agents. Query-aware context compiler.

Biological nervous systems don't recompute known workflows from scratch. Mnemon gives LLM agents the same primitive — execution memory that caches plans, not responses. 93% token reduction, 2.66ms vs 20s, zero tokens on repeat runs. LangChain, CrewAI, AutoGen.

What each LLM call really cost: prices with source and date, thinking tokens, price tiers, batch and off-peak, a ledger that never breaks your pipeline

Deterministic Context Compression & Submodular Call-Graph Pruner — Cuts LLM Bills by 75-85% in Pure Python

Simple tool to estimate AI API costs when using large language models.

The only token-saving agent rules you may need.

Ultra-lightweight (~40MB RAM), Zero-GPU Two-Stage RAG engine powered by SQLite FTS5, local FlashRank cross-encoder, and semantic caching.

Convert JSON format to TOON

Automate content research, card news, images, voice, and video from one prompt with an end-to-end Claude Code content pipeline

Top Claude Bill Optimizer (Opensource) Star if you like it!

High-efficiency Arabic text compressor and token optimizer reducing LLM token billing by 25-40% in pure PHP

Free Claude Code plugin: targeted file:line retrieval instead of whole-file reads. Measured 6–14× fewer input tokens.

Experimental CLI for estimating AI-agent request costs and tracking budget assumptions across OpenAI, Anthropic and GitHub Copilot.