Skills Directory Cleanup: ✅ NON-SKILL FILES MOVED: Proper directory organization - .windsurf/meta/: Moved REFACTORING_SUMMARY.md and SKILL_ANALYSIS.md from skills/ - .windsurf/templates/: Moved agent-templates.md and workflow-templates.md from skills/openclaw-aitbc/ - .windsurf/references/: Moved ai-operations-reference.md from skills/openclaw-aitbc/ - scripts/: Moved setup.sh from skills/openclaw-aitbc/ ✅ DEPRECATED SKILLS ARCHIVED: Clean skills directory structure - .windsurf/skills/archive/: Moved aitbc-blockchain.md, openclaw-aitbc.md, openclaw-management.md - These were legacy monolithic skills replaced by atomic skills - Archive preserves history while keeping skills directory clean ✅ SKILLS DIRECTORY NOW CONTAINS: Only atomic, production-ready skills - aitbc-ai-operator.md: AI job submission and monitoring - aitbc-marketplace-participant.md: Marketplace operations and pricing - aitbc-transaction-processor.md: Transaction execution and tracking - aitbc-wallet-manager.md: Wallet creation, listing, balance checking - openclaw-agent-communicator.md: Agent message handling and responses - openclaw-session-manager.md: Session creation and context management - archive/: Deprecated legacy skills (3 files) DIRECTORY STRUCTURE IMPROVEMENT: 🎯 Skills Directory: Contains only 6 atomic skills + archive 📋 Meta Directory: Contains refactoring analysis and summaries 📝 Templates Directory: Contains agent and workflow templates 📖 References Directory: Contains reference documentation and guides 🗂️ Archive Directory: Contains deprecated legacy skills BENEFITS: ✅ Clean Skills Directory: Only contains actual atomic skills ✅ Proper Organization: Non-skill files in appropriate directories ✅ Archive Preservation: Legacy skills preserved for reference ✅ Maintainability: Clear separation of concerns ✅ Navigation: Easier to find and use actual skills Result: Skills directory now properly organized with only atomic skills, non-skill files moved to appropriate locations, and deprecated skills archived for reference.
345 lines
11 KiB
Markdown
345 lines
11 KiB
Markdown
---
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description: OpenClaw agent management and coordination capabilities
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title: OpenClaw Agent Management Skill
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version: 1.0
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---
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# OpenClaw Agent Management Skill
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This skill provides comprehensive OpenClaw agent management, communication, and coordination capabilities. Focus on agent operations, session management, and cross-agent workflows.
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## Prerequisites
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- OpenClaw 2026.3.24+ installed and gateway running
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- Agent workspace configured: `~/.openclaw/workspace/`
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- Network connectivity for multi-agent coordination
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## Critical: Correct OpenClaw Syntax
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### Agent Commands
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```bash
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# CORRECT — always use --message (long form), not -m
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openclaw agent --agent main --message "Your task here" --thinking medium
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# Session-based communication (maintains context across calls)
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SESSION_ID="workflow-$(date +%s)"
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openclaw agent --agent main --session-id $SESSION_ID --message "Initialize task" --thinking low
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openclaw agent --agent main --session-id $SESSION_ID --message "Continue task" --thinking medium
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# Thinking levels: off | minimal | low | medium | high | xhigh
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```
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> **WARNING**: The `-m` short form does NOT work reliably. Always use `--message`.
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> **WARNING**: `--session-id` is required to maintain conversation context across multiple agent calls.
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### Agent Status and Management
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```bash
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# Check agent status
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openclaw status --agent all
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openclaw status --agent main
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# List available agents
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openclaw list --agents
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# Agent workspace management
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openclaw workspace --setup
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openclaw workspace --status
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```
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## Agent Communication Patterns
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### Single Agent Tasks
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```bash
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# Simple task execution
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openclaw agent --agent main --message "Analyze the system logs and report any errors" --thinking high
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# Task with specific parameters
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openclaw agent --agent main --message "Process this data: /path/to/data.csv" --thinking medium --parameters "format:csv,mode:analyze"
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```
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### Session-Based Workflows
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```bash
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# Initialize session
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SESSION_ID="data-analysis-$(date +%s)"
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# Step 1: Data collection
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openclaw agent --agent main --session-id $SESSION_ID --message "Collect data from API endpoints" --thinking low
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# Step 2: Data processing
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openclaw agent --agent main --session-id $SESSION_ID --message "Process collected data and generate insights" --thinking medium
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# Step 3: Report generation
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openclaw agent --agent main --session-id $SESSION_ID --message "Create comprehensive report with visualizations" --thinking high
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```
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### Multi-Agent Coordination
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```bash
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# Coordinator agent manages workflow
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openclaw agent --agent coordinator --message "Coordinate data processing across multiple agents" --thinking high
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# Worker agents execute specific tasks
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openclaw agent --agent worker-1 --message "Process dataset A" --thinking medium
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openclaw agent --agent worker-2 --message "Process dataset B" --thinking medium
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# Aggregator combines results
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openclaw agent --agent aggregator --message "Combine results from worker-1 and worker-2" --thinking high
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```
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## Agent Types and Roles
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### Coordinator Agent
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```bash
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# Setup coordinator for complex workflows
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openclaw agent --agent coordinator --message "Initialize as workflow coordinator. Manage task distribution, monitor progress, aggregate results." --thinking high
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# Use coordinator for orchestration
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openclaw agent --agent coordinator --message "Orchestrate data pipeline: extract → transform → load → validate" --thinking high
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```
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### Worker Agent
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```bash
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# Setup worker for specific tasks
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openclaw agent --agent worker --message "Initialize as data processing worker. Execute assigned tasks efficiently." --thinking medium
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# Assign specific work
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openclaw agent --agent worker --message "Process customer data file: /data/customers.json" --thinking medium
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```
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### Monitor Agent
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```bash
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# Setup monitor for oversight
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openclaw agent --agent monitor --message "Initialize as system monitor. Track performance, detect anomalies, report status." --thinking low
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# Continuous monitoring
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openclaw agent --agent monitor --message "Monitor system health and report any issues" --thinking minimal
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```
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## Agent Workflows
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### Data Processing Workflow
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```bash
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SESSION_ID="data-pipeline-$(date +%s)"
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# Phase 1: Data Extraction
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openclaw agent --agent extractor --session-id $SESSION_ID --message "Extract data from sources" --thinking medium
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# Phase 2: Data Transformation
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openclaw agent --agent transformer --session-id $SESSION_ID --message "Transform extracted data" --thinking medium
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# Phase 3: Data Loading
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openclaw agent --agent loader --session-id $SESSION_ID --message "Load transformed data to destination" --thinking medium
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# Phase 4: Validation
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openclaw agent --agent validator --session-id $SESSION_ID --message "Validate loaded data integrity" --thinking high
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```
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### Monitoring Workflow
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```bash
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SESSION_ID="monitoring-$(date +%s)"
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# Continuous monitoring loop
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while true; do
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openclaw agent --agent monitor --session-id $SESSION_ID --message "Check system health" --thinking minimal
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sleep 300 # Check every 5 minutes
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done
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```
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### Analysis Workflow
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```bash
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SESSION_ID="analysis-$(date +%s)"
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# Initial analysis
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openclaw agent --agent analyst --session-id $SESSION_ID --message "Perform initial data analysis" --thinking high
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# Deep dive analysis
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openclaw agent --agent analyst --session-id $SESSION_ID --message "Deep dive into anomalies and patterns" --thinking high
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# Report generation
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openclaw agent --agent analyst --session-id $SESSION_ID --message "Generate comprehensive analysis report" --thinking high
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```
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## Agent Configuration
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### Agent Parameters
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```bash
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# Agent with specific parameters
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openclaw agent --agent main --message "Process data" --thinking medium \
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--parameters "input_format:json,output_format:csv,mode:batch"
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# Agent with timeout
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openclaw agent --agent main --message "Long running task" --thinking high \
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--parameters "timeout:3600,retry_count:3"
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# Agent with resource constraints
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openclaw agent --agent main --message "Resource-intensive task" --thinking high \
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--parameters "max_memory:4GB,max_cpu:2,max_duration:1800"
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```
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### Agent Context Management
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```bash
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# Set initial context
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openclaw agent --agent main --message "Initialize with context: data_analysis_v2" --thinking low \
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--context "project:data_analysis,version:2.0,dataset:customer_data"
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# Maintain context across calls
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openclaw agent --agent main --session-id $SESSION_ID --message "Continue with previous context" --thinking medium
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# Update context
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openclaw agent --agent main --session-id $SESSION_ID --message "Update context: new_phase" --thinking medium \
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--context-update "phase:processing,status:active"
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```
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## Agent Communication
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### Cross-Agent Messaging
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```bash
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# Agent A sends message to Agent B
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openclaw agent --agent agent-a --message "Send results to agent-b" --thinking medium \
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--send-to "agent-b" --message-type "results"
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# Agent B receives and processes
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openclaw agent --agent agent-b --message "Process received results" --thinking medium \
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--receive-from "agent-a"
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```
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### Agent Collaboration
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```bash
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# Setup collaboration team
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TEAM_ID="team-analytics-$(date +%s)"
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# Team leader coordination
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openclaw agent --agent team-lead --session-id $TEAM_ID --message "Coordinate team analytics workflow" --thinking high
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# Team member tasks
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openclaw agent --agent analyst-1 --session-id $TEAM_ID --message "Analyze customer segment A" --thinking high
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openclaw agent --agent analyst-2 --session-id $TEAM_ID --message "Analyze customer segment B" --thinking high
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# Team consolidation
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openclaw agent --agent team-lead --session-id $TEAM_ID --message "Consolidate team analysis results" --thinking high
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```
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## Agent Error Handling
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### Error Recovery
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```bash
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# Agent with error handling
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openclaw agent --agent main --message "Process data with error handling" --thinking medium \
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--parameters "error_handling:retry_on_failure,max_retries:3,fallback_mode:graceful_degradation"
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# Monitor agent errors
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openclaw agent --agent monitor --message "Check for agent errors and report" --thinking low \
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--parameters "check_type:error_log,alert_threshold:5"
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```
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### Agent Debugging
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```bash
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# Debug mode
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openclaw agent --agent main --message "Debug task execution" --thinking high \
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--parameters "debug:true,log_level:verbose,trace_execution:true"
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# Agent state inspection
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openclaw agent --agent main --message "Report current state and context" --thinking low \
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--parameters "report_type:state,include_context:true"
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```
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## Agent Performance Optimization
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### Efficient Agent Usage
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```bash
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# Batch processing
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openclaw agent --agent processor --message "Process data in batches" --thinking medium \
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--parameters "batch_size:100,parallel_processing:true"
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# Resource optimization
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openclaw agent --agent optimizer --message "Optimize resource usage" --thinking high \
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--parameters "memory_efficiency:true,cpu_optimization:true"
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```
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### Agent Scaling
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```bash
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# Scale out work
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for i in {1..5}; do
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openclaw agent --agent worker-$i --message "Process batch $i" --thinking medium &
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done
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# Scale in coordination
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openclaw agent --agent coordinator --message "Coordinate scaled-out workers" --thinking high
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```
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## Agent Security
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### Secure Agent Operations
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```bash
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# Agent with security constraints
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openclaw agent --agent secure-agent --message "Process sensitive data" --thinking high \
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--parameters "security_level:high,data_encryption:true,access_log:true"
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# Agent authentication
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openclaw agent --agent authenticated-agent --message "Authenticated operation" --thinking medium \
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--parameters "auth_required:true,token_expiry:3600"
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```
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## Agent Monitoring and Analytics
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### Performance Monitoring
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```bash
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# Monitor agent performance
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openclaw agent --agent monitor --message "Monitor agent performance metrics" --thinking low \
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--parameters "metrics:cpu,memory,tasks_per_second,error_rate"
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# Agent analytics
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openclaw agent --agent analytics --message "Generate agent performance report" --thinking medium \
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--parameters "report_type:performance,period:last_24h"
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```
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## Troubleshooting Agent Issues
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### Common Agent Problems
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1. **Session Loss**: Use consistent `--session-id` across calls
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2. **Context Loss**: Maintain context with `--context` parameter
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3. **Performance Issues**: Optimize `--thinking` level and task complexity
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4. **Communication Failures**: Check agent status and network connectivity
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### Debug Commands
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```bash
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# Check agent status
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openclaw status --agent all
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# Test agent communication
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openclaw agent --agent main --message "Ping test" --thinking minimal
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# Check workspace
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openclaw workspace --status
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# Verify agent configuration
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openclaw config --show --agent main
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```
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## Best Practices
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### Session Management
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- Use meaningful session IDs: `task-type-$(date +%s)`
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- Maintain context across related tasks
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- Clean up sessions when workflows complete
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### Thinking Level Optimization
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- **off**: Simple, repetitive tasks
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- **minimal**: Quick status checks, basic operations
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- **low**: Data processing, routine analysis
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- **medium**: Complex analysis, decision making
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- **high**: Strategic planning, complex problem solving
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- **xhigh**: Critical decisions, creative tasks
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### Agent Organization
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- Use descriptive agent names: `data-processor`, `monitor`, `coordinator`
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- Group related agents in workflows
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- Implement proper error handling and recovery
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### Performance Tips
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- Batch similar operations
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- Use appropriate thinking levels
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- Monitor agent resource usage
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- Implement proper session cleanup
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This OpenClaw Agent Management skill provides the foundation for effective agent coordination, communication, and workflow orchestration across any domain or application.
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