← 返回
未分类 中文

Token Saver Skill

Smart token cost optimization for OpenClaw. Automatically reduces AI token consumption by 50-80% through intelligent context compression, semantic caching, a...
OpenClaw智能Token费用优化。通过智能上下文压缩、语义缓存等技术自动降低50-80%的AI Token消耗。
jzming9 jzming9 来源
未分类 clawhub v1.0.2 1 版本 99849.1 Key: 无需
★ 1
Stars
📥 1,303
下载
💾 4
安装
1
版本
#latest

概述

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

版本历史

共 1 个版本

  • v1.0.2 当前
    2026-04-30 16:50 安全 安全

安全检测

腾讯云安全 (Keen)

安全,无风险
查看报告

腾讯云安全 (Sanbu)

安全,无风险
查看报告

🔗 相关推荐

ai-agent

Self-Improving + Proactive Agent

ivangdavila
自我反思+自我批评+自我学习+自组织记忆。智能体评估自身工作、发现错误并持续改进。
★ 1,398 📥 323,143
it-ops-security

ShieldClaw

jzming9
OpenClaw安全套件,提供安全扫描、实时防护、审计日志及敏感数据加密功能。
★ 1 📥 685
ai-agent

Find Skills

guipi888
场景驱动+关键词双模式技能发现工具。当用户用自然语言描述场景/需求(如"我想做一个海报""帮我分析股票"),或明确说"安装技能/find skills/找个skill"时,自动从官方内置、本地已安装、SkillHub、虾评、GitHub、C
★ 1,474 📥 537,723