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.
11 KiB
11 KiB
description, title, version
| description | title | version |
|---|---|---|
| OpenClaw agent management and coordination capabilities | OpenClaw Agent Management Skill | 1.0 |
OpenClaw Agent Management Skill
This skill provides comprehensive OpenClaw agent management, communication, and coordination capabilities. Focus on agent operations, session management, and cross-agent workflows.
Prerequisites
- OpenClaw 2026.3.24+ installed and gateway running
- Agent workspace configured:
~/.openclaw/workspace/ - Network connectivity for multi-agent coordination
Critical: Correct OpenClaw Syntax
Agent Commands
# CORRECT — always use --message (long form), not -m
openclaw agent --agent main --message "Your task here" --thinking medium
# Session-based communication (maintains context across calls)
SESSION_ID="workflow-$(date +%s)"
openclaw agent --agent main --session-id $SESSION_ID --message "Initialize task" --thinking low
openclaw agent --agent main --session-id $SESSION_ID --message "Continue task" --thinking medium
# Thinking levels: off | minimal | low | medium | high | xhigh
Warning
: The
-mshort form does NOT work reliably. Always use--message. WARNING:--session-idis required to maintain conversation context across multiple agent calls.
Agent Status and Management
# Check agent status
openclaw status --agent all
openclaw status --agent main
# List available agents
openclaw list --agents
# Agent workspace management
openclaw workspace --setup
openclaw workspace --status
Agent Communication Patterns
Single Agent Tasks
# Simple task execution
openclaw agent --agent main --message "Analyze the system logs and report any errors" --thinking high
# Task with specific parameters
openclaw agent --agent main --message "Process this data: /path/to/data.csv" --thinking medium --parameters "format:csv,mode:analyze"
Session-Based Workflows
# Initialize session
SESSION_ID="data-analysis-$(date +%s)"
# Step 1: Data collection
openclaw agent --agent main --session-id $SESSION_ID --message "Collect data from API endpoints" --thinking low
# Step 2: Data processing
openclaw agent --agent main --session-id $SESSION_ID --message "Process collected data and generate insights" --thinking medium
# Step 3: Report generation
openclaw agent --agent main --session-id $SESSION_ID --message "Create comprehensive report with visualizations" --thinking high
Multi-Agent Coordination
# Coordinator agent manages workflow
openclaw agent --agent coordinator --message "Coordinate data processing across multiple agents" --thinking high
# Worker agents execute specific tasks
openclaw agent --agent worker-1 --message "Process dataset A" --thinking medium
openclaw agent --agent worker-2 --message "Process dataset B" --thinking medium
# Aggregator combines results
openclaw agent --agent aggregator --message "Combine results from worker-1 and worker-2" --thinking high
Agent Types and Roles
Coordinator Agent
# Setup coordinator for complex workflows
openclaw agent --agent coordinator --message "Initialize as workflow coordinator. Manage task distribution, monitor progress, aggregate results." --thinking high
# Use coordinator for orchestration
openclaw agent --agent coordinator --message "Orchestrate data pipeline: extract → transform → load → validate" --thinking high
Worker Agent
# Setup worker for specific tasks
openclaw agent --agent worker --message "Initialize as data processing worker. Execute assigned tasks efficiently." --thinking medium
# Assign specific work
openclaw agent --agent worker --message "Process customer data file: /data/customers.json" --thinking medium
Monitor Agent
# Setup monitor for oversight
openclaw agent --agent monitor --message "Initialize as system monitor. Track performance, detect anomalies, report status." --thinking low
# Continuous monitoring
openclaw agent --agent monitor --message "Monitor system health and report any issues" --thinking minimal
Agent Workflows
Data Processing Workflow
SESSION_ID="data-pipeline-$(date +%s)"
# Phase 1: Data Extraction
openclaw agent --agent extractor --session-id $SESSION_ID --message "Extract data from sources" --thinking medium
# Phase 2: Data Transformation
openclaw agent --agent transformer --session-id $SESSION_ID --message "Transform extracted data" --thinking medium
# Phase 3: Data Loading
openclaw agent --agent loader --session-id $SESSION_ID --message "Load transformed data to destination" --thinking medium
# Phase 4: Validation
openclaw agent --agent validator --session-id $SESSION_ID --message "Validate loaded data integrity" --thinking high
Monitoring Workflow
SESSION_ID="monitoring-$(date +%s)"
# Continuous monitoring loop
while true; do
openclaw agent --agent monitor --session-id $SESSION_ID --message "Check system health" --thinking minimal
sleep 300 # Check every 5 minutes
done
Analysis Workflow
SESSION_ID="analysis-$(date +%s)"
# Initial analysis
openclaw agent --agent analyst --session-id $SESSION_ID --message "Perform initial data analysis" --thinking high
# Deep dive analysis
openclaw agent --agent analyst --session-id $SESSION_ID --message "Deep dive into anomalies and patterns" --thinking high
# Report generation
openclaw agent --agent analyst --session-id $SESSION_ID --message "Generate comprehensive analysis report" --thinking high
Agent Configuration
Agent Parameters
# Agent with specific parameters
openclaw agent --agent main --message "Process data" --thinking medium \
--parameters "input_format:json,output_format:csv,mode:batch"
# Agent with timeout
openclaw agent --agent main --message "Long running task" --thinking high \
--parameters "timeout:3600,retry_count:3"
# Agent with resource constraints
openclaw agent --agent main --message "Resource-intensive task" --thinking high \
--parameters "max_memory:4GB,max_cpu:2,max_duration:1800"
Agent Context Management
# Set initial context
openclaw agent --agent main --message "Initialize with context: data_analysis_v2" --thinking low \
--context "project:data_analysis,version:2.0,dataset:customer_data"
# Maintain context across calls
openclaw agent --agent main --session-id $SESSION_ID --message "Continue with previous context" --thinking medium
# Update context
openclaw agent --agent main --session-id $SESSION_ID --message "Update context: new_phase" --thinking medium \
--context-update "phase:processing,status:active"
Agent Communication
Cross-Agent Messaging
# Agent A sends message to Agent B
openclaw agent --agent agent-a --message "Send results to agent-b" --thinking medium \
--send-to "agent-b" --message-type "results"
# Agent B receives and processes
openclaw agent --agent agent-b --message "Process received results" --thinking medium \
--receive-from "agent-a"
Agent Collaboration
# Setup collaboration team
TEAM_ID="team-analytics-$(date +%s)"
# Team leader coordination
openclaw agent --agent team-lead --session-id $TEAM_ID --message "Coordinate team analytics workflow" --thinking high
# Team member tasks
openclaw agent --agent analyst-1 --session-id $TEAM_ID --message "Analyze customer segment A" --thinking high
openclaw agent --agent analyst-2 --session-id $TEAM_ID --message "Analyze customer segment B" --thinking high
# Team consolidation
openclaw agent --agent team-lead --session-id $TEAM_ID --message "Consolidate team analysis results" --thinking high
Agent Error Handling
Error Recovery
# Agent with error handling
openclaw agent --agent main --message "Process data with error handling" --thinking medium \
--parameters "error_handling:retry_on_failure,max_retries:3,fallback_mode:graceful_degradation"
# Monitor agent errors
openclaw agent --agent monitor --message "Check for agent errors and report" --thinking low \
--parameters "check_type:error_log,alert_threshold:5"
Agent Debugging
# Debug mode
openclaw agent --agent main --message "Debug task execution" --thinking high \
--parameters "debug:true,log_level:verbose,trace_execution:true"
# Agent state inspection
openclaw agent --agent main --message "Report current state and context" --thinking low \
--parameters "report_type:state,include_context:true"
Agent Performance Optimization
Efficient Agent Usage
# Batch processing
openclaw agent --agent processor --message "Process data in batches" --thinking medium \
--parameters "batch_size:100,parallel_processing:true"
# Resource optimization
openclaw agent --agent optimizer --message "Optimize resource usage" --thinking high \
--parameters "memory_efficiency:true,cpu_optimization:true"
Agent Scaling
# Scale out work
for i in {1..5}; do
openclaw agent --agent worker-$i --message "Process batch $i" --thinking medium &
done
# Scale in coordination
openclaw agent --agent coordinator --message "Coordinate scaled-out workers" --thinking high
Agent Security
Secure Agent Operations
# Agent with security constraints
openclaw agent --agent secure-agent --message "Process sensitive data" --thinking high \
--parameters "security_level:high,data_encryption:true,access_log:true"
# Agent authentication
openclaw agent --agent authenticated-agent --message "Authenticated operation" --thinking medium \
--parameters "auth_required:true,token_expiry:3600"
Agent Monitoring and Analytics
Performance Monitoring
# Monitor agent performance
openclaw agent --agent monitor --message "Monitor agent performance metrics" --thinking low \
--parameters "metrics:cpu,memory,tasks_per_second,error_rate"
# Agent analytics
openclaw agent --agent analytics --message "Generate agent performance report" --thinking medium \
--parameters "report_type:performance,period:last_24h"
Troubleshooting Agent Issues
Common Agent Problems
- Session Loss: Use consistent
--session-idacross calls - Context Loss: Maintain context with
--contextparameter - Performance Issues: Optimize
--thinkinglevel and task complexity - Communication Failures: Check agent status and network connectivity
Debug Commands
# Check agent status
openclaw status --agent all
# Test agent communication
openclaw agent --agent main --message "Ping test" --thinking minimal
# Check workspace
openclaw workspace --status
# Verify agent configuration
openclaw config --show --agent main
Best Practices
Session Management
- Use meaningful session IDs:
task-type-$(date +%s) - Maintain context across related tasks
- Clean up sessions when workflows complete
Thinking Level Optimization
- off: Simple, repetitive tasks
- minimal: Quick status checks, basic operations
- low: Data processing, routine analysis
- medium: Complex analysis, decision making
- high: Strategic planning, complex problem solving
- xhigh: Critical decisions, creative tasks
Agent Organization
- Use descriptive agent names:
data-processor,monitor,coordinator - Group related agents in workflows
- Implement proper error handling and recovery
Performance Tips
- Batch similar operations
- Use appropriate thinking levels
- Monitor agent resource usage
- Implement proper session cleanup
This OpenClaw Agent Management skill provides the foundation for effective agent coordination, communication, and workflow orchestration across any domain or application.