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- Add status fields to Receipt model (status, claimed_at, claimed_by) - Add RECEIPT_CLAIM handling to state_transition.py with validation and reward minting - Add type field to Transaction model for reliable transaction type storage - Update router to use TransactionRequest model to preserve type field - Update poa.py to extract type from mempool transaction content and store only original payload - Add RECEIPT_CLAIM to GasType enum with gas schedule
6.3 KiB
6.3 KiB
description, title, version
| description | title | version |
|---|---|---|
| Atomic OpenClaw agent testing with deterministic communication validation and performance metrics | openclaw-agent-testing-skill | 1.1 |
OpenClaw Agent Testing Skill
Purpose
Test and validate OpenClaw agent functionality, communication patterns, session management, and performance with deterministic validation metrics.
Activation
Trigger when user requests OpenClaw agent testing: agent functionality validation, communication testing, session management testing, or agent performance analysis.
Input
{
"operation": "test-agent-communication|test-session-management|test-agent-performance|test-multi-agent|comprehensive",
"agent": "main|specific_agent_name (default: main)",
"test_message": "string (optional for communication testing)",
"session_id": "string (optional for session testing)",
"thinking_level": "off|minimal|low|medium|high|xhigh",
"test_duration": "number (optional, default: 60 seconds)",
"message_count": "number (optional, default: 5)",
"concurrent_agents": "number (optional, default: 2)"
}
Output
{
"summary": "OpenClaw agent testing completed successfully",
"operation": "test-agent-communication|test-session-management|test-agent-performance|test-multi-agent|comprehensive",
"test_results": {
"agent_communication": "boolean",
"session_management": "boolean",
"agent_performance": "boolean",
"multi_agent_coordination": "boolean"
},
"agent_details": {
"agent_name": "string",
"agent_status": "online|offline|error",
"response_time": "number",
"message_success_rate": "number"
},
"communication_metrics": {
"messages_sent": "number",
"messages_received": "number",
"average_response_time": "number",
"communication_success_rate": "number"
},
"session_metrics": {
"sessions_created": "number",
"session_preservation": "boolean",
"context_maintenance": "boolean",
"session_duration": "number"
},
"performance_metrics": {
"cpu_usage": "number",
"memory_usage": "number",
"response_latency": "number",
"throughput": "number"
},
"issues": [],
"recommendations": [],
"confidence": 1.0,
"execution_time": "number",
"validation_status": "success|partial|failed"
}
Process
1. Analyze
- Validate agent testing parameters and operation type
- Check OpenClaw service availability and health
- Verify agent availability and status
- Assess testing scope and requirements
2. Plan
- Prepare agent communication test scenarios
- Define session management testing strategy
- Set performance monitoring and validation criteria
- Configure multi-agent coordination tests
3. Execute
- Test agent communication with various thinking levels
- Validate session creation and context preservation
- Monitor agent performance and resource utilization
- Test multi-agent coordination and communication patterns
4. Validate
- Verify agent communication success and response quality
- Check session management effectiveness and context preservation
- Validate agent performance metrics and resource usage
- Confirm multi-agent coordination and communication patterns
Constraints
- MUST NOT test unavailable agents without explicit request
- MUST NOT exceed message length limits (4000 characters)
- MUST validate thinking level compatibility
- MUST handle communication timeouts gracefully
- MUST preserve session context during testing
- MUST provide deterministic performance metrics
Environment Assumptions
- OpenClaw 2026.3.24+ installed and gateway running
- Agent workspace configured at
~/.openclaw/workspace/ - Network connectivity for agent communication
- Default agent available: "main"
- Session management functional
Error Handling
- Agent unavailable → Return agent status and availability recommendations
- Communication timeout → Return timeout details and retry suggestions
- Session management failures → Return session diagnostics and recovery steps
- Performance issues → Return performance metrics and optimization recommendations
Example Usage Prompt
Run comprehensive OpenClaw agent testing including communication, session management, performance, and multi-agent coordination validation
Expected Output Example
{
"summary": "Comprehensive OpenClaw agent testing completed with all systems operational",
"operation": "comprehensive",
"test_results": {
"agent_communication": true,
"session_management": true,
"agent_performance": true,
"multi_agent_coordination": true
},
"agent_details": {
"agent_name": "main",
"agent_status": "online",
"response_time": 2.3,
"message_success_rate": 100.0
},
"communication_metrics": {
"messages_sent": 5,
"messages_received": 5,
"average_response_time": 2.1,
"communication_success_rate": 100.0
},
"session_metrics": {
"sessions_created": 3,
"session_preservation": true,
"context_maintenance": true,
"session_duration": 45.2
},
"performance_metrics": {
"cpu_usage": 15.3,
"memory_usage": 85.2,
"response_latency": 2.1,
"throughput": 2.4
},
"issues": [],
"recommendations": ["All agents operational", "Communication latency optimal", "Session management effective"],
"confidence": 1.0,
"execution_time": 67.3,
"validation_status": "success"
}
Model Routing Suggestion
Fast Model (Claude Haiku, GPT-3.5-turbo)
- Simple agent availability checking
- Basic communication testing with low thinking
- Quick agent status validation
Reasoning Model (Claude Sonnet, GPT-4)
- Comprehensive agent communication testing
- Session management validation and optimization
- Multi-agent coordination testing and analysis
- Complex agent performance diagnostics
Coding Model (Claude Sonnet, GPT-4)
- Agent performance optimization algorithms
- Communication pattern analysis and improvement
- Session management enhancement strategies
Performance Notes
- Execution Time: 5-15 seconds for basic tests, 30-90 seconds for comprehensive testing
- Memory Usage: <150MB for agent testing operations
- Network Requirements: OpenClaw gateway connectivity
- Concurrency: Safe for multiple simultaneous agent tests with different agents
- Session Management: Automatic session creation and context preservation testing