v2.7.2 · Apache-2.0
Content-aware output compression for AI coding assistants. 36 specialized processors cut CLI output tokens by 60-99% (git, pytest, npm, terraform, kubectl, docker, and more) without losing errors, diffs, or stack traces.
v4.9.2 · MIT
Claude Code plugin that tracks token usage, identifies wasted context, and saves 30-50% on API costs. Heatmaps, ROI reports, budget alerts, efficiency scores, git-aware suggestions — all local, zero config.
v3.0.0 · MIT
MCP server that lets Claude Code delegate heavy-token tasks to DeepSeek, Kimi, GLM, Qwen, Grok, or any OpenAI-compatible model. Claude orchestrates; the delegate does the heavy lifting. Zero dependencies.