LG Token Saver

LG-token-saver
Save 87% token usage. One file. Zero install.
by 廖工 (LiaoGong) / CC杰 · 廖工AI设计实战
Input + Output + Context — three layers of optimization in a single Claude Code Skill

Why Token Saver?

Claude Code burns tokens on verbose output, redundant searches, unfiltered Bash output, and context bloat. Other tools fix one layer — Token Saver covers all three.

Quick Start

Auto-activates. No config. 87% savings from the first message.

Three modes, toggle anytime:
- 🟢 Lite (~65%) — Invisible, no behavior change
- 🟡 Full (~80%) — Default, balanced
- 🔴 Ultra (~87%) — Maximum, every trick enabled

Real Benchmarks

Single article build session — 6 steps, cross-directory search, Bash output, parallel agents:

Real-World Example: One Article, One Command

Here's what actually happens when building a WeChat article with and without Token Saver:

Scenario: Cross-directory research + Bash build + parallel agents

Without optimization (raw Claude Code):

With Token Saver (Full mode):

Result: 198,000 → 15,500 tokens = 92% savings. Same task, same output, zero quality loss.

Why Token Saver Wins Where Others Fall Short

The other tools fix 1/3 of the problem. Token Saver fixes all 3.

Features

Multi-Scenario Savings (6 months verified)

Weighted average: 87%. Not cherry-picked. Real sessions, real data.

License

MIT · by LiaoGong / CC杰

About the Author

廖工 (LiaoGong) / CC杰 is an AI tool builder based in China.

When Claude Code launched, developers outside supported regions couldn't use it. So he built cc-switch (20K+ stars) — a one-click proxy that routes Claude Code through domestic AI APIs, making it accessible to millions of Chinese developers.

Then he automated his own workflow. His article pipeline turns python build.py into a complete WeChat article with…