Token Saver Skill

Smart token cost optimization for OpenClaw. Automatically reduces AI token consumption by 50-80% through intelligent context compression, semantic caching, and adaptive optimization while maintaining response quality.

TokenSaver

A token cost optimization skill that helps you save 50-80% on AI token usage without sacrificing response quality.

When to Use

Use TokenSaver when:

• You have long conversations that consume many tokens
• You want to reduce AI API costs
• You're working with technical discussions that accumulate context
• You notice token usage growing rapidly in long sessions

Core Capabilities

1. Smart Context Compression

Automatically compresses conversation history based on message importance.

How it works:

• Recent messages (last 3-5) kept fully intact
• Older messages summarized based on importance score
• Code blocks and critical decisions never compressed

Savings: 50-70% reduction in context tokens

2. Semantic Cache

Caches responses to similar queries to avoid reprocessing.

How it works:

• L1: Exact query match → 100% savings
• L2: Semantic similarity > 85% → 80% savings
• L3: Pattern match → 50% savings

3. Adaptive Optimization

Automatically adjusts compression based on token pressure.

Stages:

• < 3K tokens: No compression
• 3-6K tokens: Light compression
• 6-10K tokens: Medium compression

• 10K tokens: Heavy compression + suggest new chat

Natural Language Commands

When user asks about TokenSaver in natural language, interpret and execute:

Settings & Configuration

User says: "Configure TokenSaver" / "TokenSaver settings" / "Setup TokenSaver" Action: Show current configuration and available options

Current TokenSaver Settings:
- Mode: Adaptive (auto-adjust based on token pressure)
- Compression: Balanced
- Cache: Enabled
- Quality Threshold: 85%

You can change mode:
- /tokensave - Aggressive mode (max savings)
- /tokenbalance - Balanced mode (default)
- /tokenquality - Quality priority (min compression)

User says: "Use aggressive mode" / "Maximize savings" / "Set to save mode" Action: Execute /tokensave command Response: "✅ TokenSaver switched to aggressive save mode. This provides maximum token savings (up to 80%) with slight quality trade-off."

User says: "Use balanced mode" / "Default settings" / "Set to balanced" Action: Execute /tokenbalance command Response: "✅ TokenSaver switched to balanced mode. Good savings (50-70%) with quality preserved."

User says: "Prioritize quality" / "Keep full context" / "Set to quality mode" Action: Execute /tokenquality command Response: "✅ TokenSaver switched to quality priority mode. Minimal compression, maximum context retention for precision-critical tasks."

User says: "Disable TokenSaver" / "Turn off token saving" / "Stop TokenSaver" Action: Execute /tokenoff command Response: "⏸️ TokenSaver temporarily disabled. Re-enable anytime with /tokens or by asking me to turn it back on."

Usage Reports & Analytics

User says: "Show me token usage report" / "TokenSaver statistics" / "Token report" Action: Execute /tokenreport command Response format:

📈 TokenSaver Usage Report
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
This Session:
• Total Original Tokens: 12,450
• Total Optimized Tokens: 4,358
• Tokens Saved: 8,092 (65%)
• Estimated Cost Saved: $0.016
• Cache Hits: 5
• Compressions Applied: 12

Top Savings Sources:
1. Context Compression: -6,200 tokens
2. Semantic Cache: -1,500 tokens
3. Response Optimization: -392 tokens

User says: "TokenSaver status" / "How much am I saving?" / "Token status" Action: Execute /tokens command Response format:

💰 TokenSaver Status
━━━━━━━━━━━━━━━━━━━━
Current Session:
• Savings: 65%
• Original Tokens: 12,450
• Optimized Tokens: 4,358
• Cache Hits: 5

Current Mode: Balanced (Adaptive)
• Stage 3 compression active
• Quality Score: 95%

User says: "Clear token cache" / "Reset cache" / "Clear TokenSaver cache" Action: Execute /tokencache clear command Response: "✅ TokenSaver cache cleared. Fresh responses will be generated for subsequent queries."

Explanation & Help

User says: "What is TokenSaver" / "How does token saving work?" / "Explain TokenSaver" Response:

TokenSaver is an intelligent token cost optimization skill that helps you save 50-80% on AI token usage.

Key Features:
1. Smart Context Compression - Summarizes old conversation while keeping recent messages intact
2. Semantic Cache - Reuses responses for similar questions
3. Adaptive Optimization - Automatically adjusts based on conversation length
4. Quality Guard - Never compresses code, errors, or important messages

Benefits:
• Save 50-80% on token costs
• Faster responses with caching
• No quality loss for critical content
• Automatic - works in background

User says: "TokenSaver not working" / "Why no savings?" / "TokenSaver not saving" Response:

TokenSaver may not show savings if:
1. Conversation is too short (< 3000 tokens) - compression starts at 3K
2. Currently in quality priority mode - switch with /tokensave
3. First-time queries - cache builds up over time
4. Code-heavy conversation - code blocks are never compressed

Try starting a longer technical discussion to see significant savings!

Best Practices

User says: "TokenSaver best practices" / "How to use TokenSaver effectively?" / "TokenSaver tips" Response:

TokenSaver Best Practices:

1. For Debugging/Code Review:
   Use /tokenquality mode to keep full context

2. For Research/Exploration:
   Use /tokensave mode for maximum savings (up to 80%)

3. For General Chat:
   Balanced mode (default) works best

4. When to Start New Chat:
   If switching major topics, start fresh for better compression

5. Monitor with:
   /tokens - Quick status check
   /tokenreport - Detailed analytics

Slash Commands

For direct command access:

/tokens

Show current status and statistics

Session Savings: 65%
Original Tokens: 12,450
Optimized Tokens: 4,358
Cache Hits: 3

/tokensave

Enable aggressive save mode

• Maximum compression
• Best for very long technical discussions
• Slight quality trade-off possible

/tokenbalance

Balanced mode (default)

• Good savings with quality preserved
• Recommended for most use cases

/tokenquality

Quality priority mode

• Minimal compression
• Maximum context retention
• Use when precision is critical

/tokenreport

Generate detailed usage report

Total Tokens Saved: 8,092
Estimated Cost Saved: $0.016
Compressions Applied: 12
Cache Hits: 5

/tokencache clear

Clear all cached responses

/tokenoff

Temporarily disable optimization

Usage Examples

Example 1: Long coding session

User: [20 rounds of Python discussion]
TokenSaver: Optimized 15K → 4.5K tokens (70% saved)

Example 2: Repeated questions

User: "How do I write to a file in Python?"
User: "Python file write method?"
TokenSaver: L2 cache hit - instant response, 0 tokens used

Example 3: Topic switching

User: Switching from discussing Python to JavaScript...
TokenSaver: "Detected topic change. Start new chat to keep context clean?"
[Yes] [No]

Safety Features

TokenSaver never compresses:

• Code blocks (always kept intact)
• Error messages and stack traces
• User-marked important messages
• Messages with high cross-references

Quality Guard:

• Auto-rollback if quality drops > 15%
• One-click restore to uncompressed version
• Snapshots for every compression

Configuration

Default configuration:

{
  "mode": "adaptive",
  "compression": "balanced",
  "cache": true,
  "qualityThreshold": 0.85
}

Expected Results

Conversation Type	Tokens Saved	Quality Impact
Technical discussion (50 rounds)	70%	Minimal
Code review	80%	None
Casual chat	75%	None
Quick Q&A	30-50%	None

Limitations

• Requires conversation to exceed 3K tokens before compression starts
• First-time queries cannot be cached
• Very short conversations (< 10 messages) see minimal benefit
• Code-heavy conversations benefit most from smart referencing

Related Skills

• shieldclaw: For security scanning
• browser_visible: For web browsing
• file_reader: For reading local files