token-optimizer

The 30-Second Version

Token Optimizer cuts the tokens your AI coding assistant wastes, keeps your work alive across sessions and compactions, and shows you where every dollar went on a live dashboard. Most of it runs automatically. You install it, run the audit once, and the hooks do the rest.

Why not just use Headroom or RTK? They compress command output, which covers 15-25% of your context. Token Optimizer covers that plus the other 75%: bloated configs, unused skills, stale memory, compaction loss, model misrouting, behavioral waste. Every saving is cache-safe and measured. The dashboard updates after every session, automatically.

Works on Claude Code (CLI and VS Code), OpenCode, OpenClaw, Codex, Hermes, and GitHub Copilot (beta). Windsurf and Cursor are next on the roadmap.

Install

Claude Code (recommended):

/plugin marketplace add alexgreensh/token-optimizer
/plugin install token-optimizer@alexgreensh-token-optimizer

Then in Claude Code: /token-optimizer

Enable auto-update after installing. Claude Code ships third-party marketplaces with auto-update off by default. /plugin → Marketplaces tab → select alexgreensh-token-optimizer → Enable auto-update. One-time, 10 seconds.

After install, run /token-optimizer once to set up hooks. From there, everything runs automatically: compression, checkpoints, quality scoring, dashboard updates. You don't need to run any command again unless you want an audit.

Codex:

codex plugin marketplace add alexgreensh/token-optimizer

Then in the Codex TUI: /plugins and install Token Optimizer. See docs/codex.md.

OpenCode: add token-optimizer-opencode to the plugin array in your opencode.json:

{ "$schema": "https://opencode.ai/config.json", "plugin": ["token-optimizer-opencode"] }

See opencode/README.md.

OpenClaw:

openclaw plugins install github:alexgreensh/token-optimizer

See openclaw/README.md.

Hermes:

git clone https://github.com/alexgreensh/token-optimizer.git
token-optimizer/install.sh --hermes

See hermes/README.md.

GitHub Copilot (beta):

git clone --depth 1 https://github.com/alexgreensh/token-optimizer.git
cd token-optimizer
bash install.sh --copilot

See docs/copilot.md.

macOS/Linux script install (alternative to plugin):

tmp="$(mktemp -d)"
release_json="$(curl -fsSL https://api.github.com/repos/alexgreensh/token-optimizer/releases/latest)"
tag="$(python3 -c 'import json,sys; print(json.load(sys.stdin)["tag_name"])' <<<"$release_json")"
git clone --branch "$tag" --depth 1 https://github.com/alexgreensh/token-optimizer.git ~/.claude/token-optimizer
bash ~/.claude/token-optimizer/install.sh
rm -rf "$tmp"

Windows users: Use the plugin install only. Do not run install.sh on Windows. If you hit EBUSY errors, close all Claude Code and Git Bash windows, kill lingering git.exe processes, delete C:\Users\<you>\.claude\token-optimizer and C:\Users\<you>\.claude\plugins\marketplaces\alexgreensh-token-optimizer, then retry.

If install.sh fails with $'\r': command not found (a clone made before LF line endings were enforced converted the script to CRLF), strip the carriage returns once and re-run — the repo now ships a .gitattributes that prevents this on fresh clones:

sed -i 's/\r$//' ~/.claude/token-optimizer/install.sh
# already have the repo? re-normalize line endings in place:
git -C ~/.claude/token-optimizer add --renormalize . && git -C ~/.claude/token-optimizer checkout -- .

Token Optimizer is additive and reversible. Every runtime has a clean uninstall that removes only what we installed, leaving your own hooks, config, and session data intact. Full per-runtime steps live in docs/uninstall.md.

Quickest path (Claude Code plugin install):

/plugin uninstall token-optimizer@alexgreensh-token-optimizer

What You Get

Runs automatically, every session, you do nothing:

• 🔄 Smart Compaction: checkpoints before auto-compact, restores after
• 🗄️ Session Continuity: cross-session hints, cold-resume, checkpoint scoring
• 📦 Active Compression: 9 features, all on by default (delta diffs, skeletons, bash/search compression, lean-output nudges, quality nudges, loop detection, activity mode, decision extraction)
• 📊 Quality Scoring: 7 signals, real-time, letter grades S–F
• 🗃️ Session Database: SQLite, 15 tables, full audit trail, zero network
• 🔍 Progressive Disclosure: large outputs archived, expand on demand
• 🧠 Context Intel Digest: post-compaction re-orientation without re-reads
• 🔀 Model Routing Nudges: steers to the right tier for the task

When you ask for it:

• 🩺 /token-optimizer: full audit with guided fixes
• 📈 /token-coach: 30-day trend analysis with specific fixes
• ⚡ quick: 10-second health check
• 🔧 doctor: installation check
• 💰 savings: dollar savings report
• 📋 report: per-component token breakdown
• 🌐 `dash