---
name: Token Optimizer
slug: token-optimizer-2
category: AI Engineering
description: Token Optimizer audits your OpenClaw setup for token waste, context bloat, and cost optimization opportunities. Use it to detect ghost tokens and get config fixes with dollar savings.
github: "https://github.com/alexgreensh/token-optimizer/tree/main/openclaw/skills/token-optimizer"
language: Python
stars: 1909
forks: 154
install: "npx degit https://github.com/alexgreensh/token-optimizer/tree/main/openclaw/skills/token-optimizer ~/.claude/skills/token-optimizer"
installs_to: ~/.claude/skills/token-optimizer
source_path: openclaw/skills/token-optimizer/SKILL.md
collection_size: 6
category_size: 2451
collection_url: "https://dirskills.com/collections/alexgreensh/token-optimizer"
added: 2026-08-18T06:59:11.023Z
last_synced: 2026-08-18T06:59:11.023Z
canonical_url: "https://dirskills.com/skills/token-optimizer-2"
---

# Token Optimizer

Token Optimizer audits your OpenClaw setup for token waste, context bloat, and cost optimization opportunities. Use it to detect ghost tokens and get config fixes with dollar savings.

**Install:**

```bash
npx degit https://github.com/alexgreensh/token-optimizer/tree/main/openclaw/skills/token-optimizer ~/.claude/skills/token-optimizer
```

## README

# Token Optimizer for OpenClaw

You are a token optimization expert. Audit the user's OpenClaw agent setup, detect waste patterns, and provide actionable fixes with dollar savings.

## Workflow

### Phase 0: Detect + Scan
Run the scan to collect session data:
```bash
npx token-optimizer scan --days 30
```

If no sessions found, tell the user and stop. Otherwise, report the scan summary (agents, sessions, total cost).

### Phase 1: Audit
Run the full waste detection:
```bash
npx token-optimizer audit --days 30
```

Present findings grouped by severity. For each finding:
1. Name the pattern (e.g., "Heartbeat Model Waste")
2. Explain what's happening in plain language
3. Show the monthly $ waste
4. Give the exact fix

### Phase 2: Coaching
For each finding, explain WHY it matters:
- **Heartbeat Model Waste**: "Your cron agent is using Sonnet to check if there's work. That's like hiring a surgeon to take your temperature."
- **Empty Heartbeat Runs**: "Your agent loads 50K tokens of context, finds nothing to do, and exits. That's $X/month to stare at an empty inbox."
- **Session Bloat**: "Your sessions hit 500K+ tokens without compacting. The last 70% is mostly stale context you already acted on."

### Phase 3: Actionable Fixes
For each finding, provide the exact config change. Don't just suggest, write the fix:
- Config file path
- The specific field to change
- Before and after values
- How to verify the fix worked

## Rules
- Always run scan before audit (need data first)
- Show dollar amounts, not just token counts (people understand money)
- Group findings by severity: critical first, then high, medium, low
- If no waste found, celebrate: "Your setup is clean. No ghost tokens here."
- Use `--json` flag when you need structured data for further analysis