Skip to content

CLAW_SELF_OPTIMIZATION_STRATEGY.md

Latest commit

 

History

History
326 lines (245 loc) · 8.07 KB

CLAW_SELF_OPTIMIZATION_STRATEGY.md

File metadata and controls

326 lines (245 loc) · 8.07 KB
Raw

CLAW Self-Optimization Strategy

Based on Analysis of 18 Reels + 5 YouTube Videos

🎯 IMMEDIATE IMPROVEMENTS (Implement Today)

1. TOKEN OPTIMIZATION (97% Cost Reduction)

Current Problem:

  • Loading full context files on every heartbeat
  • Session history bloat (111KB per prompt observed)
  • No model routing (everything goes to Opus/Sonnet)

Solutions:

A. Context Trimming

# Add to config: Don't load full SOUL.md on heartbeats
# Create lightweight heartbeat-context.md (5KB vs 50KB)

Implementation:

  • Create contexts/heartbeat-minimal.md — 5KB essentials only
  • Create contexts/full-context.md — Full 50KB version for deep work
  • Route heartbeats → minimal context
  • Route user requests → full context

B. Session History Management

# Create "newsession" command that:
# 1. Archives current session to memory/YYYY-MM-DD.md
# 2. Clears active session buffer
# 3. Prevents 111KB upload every prompt

Expected Savings: $2-3/day just on idle heartbeats

2. MULTI-MODEL ROUTING (85% Haiku / 10% Sonnet / 5% Opus)

Current: Default model for everything (moonshot/kimi-k2.5)

Optimized Routing:

Task Type Model Cost Use Case
Heartbeats Ollama (local) FREE System checks, status pings
File ops Haiku ~$0.0001 Move files, CSV compilation
Web fetch Haiku ~$0.0002 Simple extracts, searches
Coding Sonnet ~$0.003 Complex logic, debugging
Deep reasoning Opus ~$0.05 Business strategy, analysis

Implementation:

{
  "modelRouting": {
    "heartbeat": "ollama/llama3.2",
    "fileOperations": "anthropic/claude-sonnet-4",
    "webFetch": "anthropic/claude-haiku-3",
    "coding": "anthropic/claude-sonnet-4",
    "deepAnalysis": "anthropic/claude-opus-4"
  }
}

3. OPENROUTER INTEGRATION (Free Tier Access)

What: Unified API for 300+ models with free tier URL: https://openrouter.ai

Free Models Available:

  • openrouter/free — Auto-selects free model
  • meta-llama/llama-3.2-3b-instruct:free — Good for heartbeats
  • google/gemini-flash-1.5:free — Fast responses
  • mistralai/mistral-7b-instruct:free — General tasks

Benefits:

  • No single provider lock-in
  • Fallback models if one fails
  • Cost comparison across providers
  • Free tier: 20 requests/min, 200 requests/day

Implementation:

# Add to environment
OPENROUTER_API_KEY=your_key_here

# Use in config
{
  "defaultModel": "openrouter/meta-llama/llama-3.2-3b-instruct",
  "fallbackModel": "openrouter/google/gemini-flash-1.5"
}

4. OLLAMA LOCAL LLM (Zero-Cost Heartbeats)

Setup:

# Install Ollama
brew install ollama

# Pull lightweight model (1.2GB)
ollama pull llama3.2

# Test
ollama run llama3.2 "System check: all good?"

Integration:

// heartbeat hook
if (message.type === 'heartbeat') {
  return await ollama.generate({
    model: 'llama3.2',
    prompt: 'Check system status. Reply "HEARTBEAT_OK" if nothing urgent.'
  });
}

Savings: $2-3/day → $0/day for heartbeats

🔧 NEW SKILLS TO CREATE

Skill 1: token-optimizer

Purpose: Automatically optimize token usage

Features:

  • Monitor daily token spend
  • Alert if >$5/day
  • Auto-switch to cheaper models for routine tasks
  • Report: "Today's usage: $1.20 (saved $3.80 vs baseline)"

Hook: Pre-request routing based on complexity

Skill 2: model-router

Purpose: Intelligent model selection

Logic:

IF task.contains("code", "debug", "build") → Sonnet
IF task.contains("analyze", "strategy", "research") → Opus
IF task.contains("move", "copy", "organize", "heartbeat") → Ollama/Haiku
IF task.contains("fetch", "search", "summarize") → Haiku

Hook: Intercept all model calls, route intelligently

Skill 3: openrouter-bridge

Purpose: Access 300+ models via single API

Capabilities:

  • Try free models first
  • Fallback to paid if free rate-limited
  • Cost tracking per request
  • Model comparison: "Task X cost $0.02 on Sonnet, would be $0.005 on Haiku"

Skill 4: session-manager

Purpose: Prevent session history bloat

Commands:

  • newsession — Archive current, start fresh
  • sessionstatus — Show current session size
  • autosession — Auto-archive every 2 hours

Hook: Auto-archive before heavy tasks

🔌 MCP SERVERS TO INTEGRATE

What is MCP?

Model Context Protocol — standardized way for AI to use tools OpenAI adopted March 2025, Claude supports via plugins

High-Value MCP Servers:

1. Filesystem MCP

  • Secure file operations
  • Better than direct shell access
  • Read/write with permissions

2. Brave Search MCP

  • Web search without scraping
  • $0.005/search vs API costs
  • Better than curl + parse

3. GitHub MCP

  • Read repos, issues, PRs
  • Create branches, commits
  • Better than gh CLI for complex ops

4. Apify MCP

  • Direct integration with scrapers
  • No Python scripts needed
  • Already have account (0motionguy)

5. Token Tracker MCP

  • Real-time usage monitoring
  • Per-session cost tracking
  • Alert on anomalies

Registry: https://registry.modelcontextprotocol.io/

📊 POLYMARKET TRADING INSIGHTS

From Video Analysis:

Trader made $247/day with $100 using "Lillian"

System Components:

  1. Wallet Tracking — 20,000+ wallets monitored
  2. Signals Dashboard — Outliers with high P&L, low visibility
  3. Twitter Intel — 24/7 monitoring for trending topics
  4. Content Generation — Auto-create viral-style posts

Opportunity:

  • Build similar dashboard for our trading
  • Track 25 high-performing wallets
  • Find outliers before they go viral
  • Generate content about winning strategies

Skills to Build:

  • polymarket-intel — Wallet tracking dashboard
  • trading-signals — Outlier detection
  • viral-content-gen — Auto-create trading posts

🚀 IMPLEMENTATION PRIORITY

Week 1: Cost Optimization

  1. Install Ollama, pull llama3.2
  2. Configure heartbeat → local LLM
  3. Create session-manager skill
  4. Test: Monitor daily spend

Week 2: Model Routing

  1. Create model-router skill
  2. Define task→model mappings
  3. Test with 50/50 split
  4. Measure cost reduction

Week 3: OpenRouter + MCP

  1. Sign up OpenRouter (free tier)
  2. Install 3 MCP servers
  3. Create openrouter-bridge skill
  4. Full integration test

Week 4: Advanced Features

  1. Polymarket intel dashboard
  2. Token optimizer alerts
  3. Viral content generator
  4. Full automation workflow

💡 KEY INSIGHTS FROM ANALYSIS

1. Token Burn is Real

  • Matt Ganzac: Was burning $90/month just idling
  • Fixed: 97% reduction with local LLM + smart routing
  • Our current: Unknown, need monitoring

2. Free Tier Opportunities

  • OpenRouter: 200 requests/day free
  • Ollama: Unlimited local inference
  • Apify: $5/month credit (already have)
  • GitHub API: 5,000 requests/hour free

3. Security First

  • @softgirlnocode: "Don't connect email day 1"
  • Use isolated machine/VPS for sensitive ops
  • Mac Mini trend = dedicated hardware

4. Multi-Agent Teams

  • 14 sub-agents working together: $6 for 6 hours
  • vs Single Opus: $150 for same work
  • Parallel processing = massive savings

5. Content Farming Goldmine

  • Viral Polymarket posts = engagement bait
  • Affiliate links hidden in "success stories"
  • Opportunity: Create legit analysis, capture traffic

🎯 IMMEDIATE ACTION ITEMS

Today:

  1. Install Ollama: brew install ollama
  2. Pull model: ollama pull llama3.2
  3. Test heartbeat: Create minimal context file
  4. Check current token usage: Review Anthropic dashboard

This Week:

  1. Build session-manager skill
  2. Configure model routing
  3. Sign up OpenRouter
  4. Install 3 MCP servers

Expected Outcome:

  • 80-90% cost reduction
  • Faster response times (local LLM for simple tasks)
  • Better reliability (fallback models)
  • New revenue opportunities (Polymarket intel)

Document Created: 2026-02-09 Based on: 18 Instagram Reels + 5 YouTube transcripts Next Review: After implementation Week 1