How to Fix OpenClaw Context Window Errors

# Enable context size logging:
export OPENCLAW_LOG_CONTEXT_SIZE=true
systemctl restart openclaw

# Check recent context sizes in logs:
grep "context_tokens" ~/.openclaw/logs/openclaw.log | tail -20

# Example output:
# context_tokens=45231 max_tokens=100000 utilization=45%

# Or query via API if available:
curl http://localhost:3000/api/conversation/stats | jq .context_size

# Edit OpenClaw config:
nano ~/.openclaw/.env

# Add or update:
ENABLE_CONTEXT_COMPACTION=true
COMPACTION_THRESHOLD=0.7  # Trigger at 70% of max
MAX_CONTEXT_TOKENS=90000  # Leave headroom under model max

# Choose compaction strategy:
COMPACTION_STRATEGY=summarize  # Options: summarize, truncate, sliding_window

# Configure summarization model (use cheaper/faster):
COMPACTION_MODEL=claude-3-haiku-20240307

# Restart to apply:
systemctl restart openclaw

# Set per-model context limits in config:
cat >> ~/.openclaw/config.json << 'EOF'
{
  "models": {
    "claude-3-5-sonnet-20241022": {
      "max_context_tokens": 180000
    },
    "gpt-4-turbo": {
      "max_context_tokens": 120000
    },
    "claude-3-haiku-20240307": {
      "max_context_tokens": 180000
    }
  }
}
EOF

# Or in .env for global limit:
MAX_CONTEXT_LENGTH=100000  # Apply to all models

# Configure auto-summarization:
nano ~/.openclaw/.env

# Add:
ENABLE_CONVERSATION_SUMMARIZATION=true
SUMMARIZATION_TRIGGER_TOKENS=50000
SUMMARIZATION_PRESERVE_RECENT=20  # Keep last 20 messages

# Summarization prompt (customize if needed):
SUMMARIZATION_PROMPT="Summarize the above conversation, preserving key facts, decisions, and context needed for future messages."

# Test summarization manually:
curl -X POST http://localhost:3000/api/conversation/summarize \
  -H "Content-Type: application/json" \
  -d '{"conversation_id": "abc123"}'

# For file-reading skills, set max output:
SKILL_FILE_READ_MAX_CHARS=5000
SKILL_FILE_READ_TRUNCATE=true

# For web scraping skills:
SKILL_WEB_SCRAPE_MAX_TOKENS=2000

# For code execution skills:
SKILL_CODE_OUTPUT_MAX_LINES=100

# General skill output limit:
SKILL_MAX_OUTPUT_TOKENS=3000

# Skills exceeding limit will truncate with:
# "... (output truncated, 15000 more chars)"

# Models with large context windows (as of 2025):
# - Claude 3.5 Sonnet: 200K tokens
# - Claude 3 Opus: 200K tokens
# - GPT-4 Turbo: 128K tokens
# - Gemini 1.5 Pro: 1M tokens

# Update default model in .env:
nano ~/.openclaw/.env
DEFAULT_MODEL=claude-3-5-sonnet-20241022

# Check available models:
curl http://localhost:3000/api/models