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Implement RECEIPT_CLAIM transaction type 
- 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
2026-04-22 13:35:31 +02:00

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description, title, version
description title version
Atomic OpenClaw multi-agent workflow coordination with deterministic outputs openclaw-coordination-orchestrator 1.1

OpenClaw Coordination Orchestrator

Purpose

Coordinate multi-agent workflows, manage agent task distribution, and orchestrate complex operations across multiple OpenClaw agents.

Activation

Trigger when user requests multi-agent coordination: task distribution, workflow orchestration, agent collaboration, or parallel execution management.

Input

{
  "operation": "distribute|orchestrate|collaborate|monitor",
  "agents": ["agent1", "agent2", "..."],
  "task_type": "analysis|execution|validation|testing",
  "workflow": "string (optional for orchestrate)",
  "parallel": "boolean (optional, default: true)"
}

Output

{
  "summary": "Multi-agent coordination completed successfully",
  "operation": "distribute|orchestrate|collaborate|monitor",
  "agents_assigned": ["agent1", "agent2", "..."],
  "task_distribution": {
    "agent1": "task_description",
    "agent2": "task_description"
  },
  "workflow_status": "active|completed|failed",
  "collaboration_results": {},
  "issues": [],
  "recommendations": [],
  "confidence": 1.0,
  "execution_time": "number",
  "validation_status": "success|partial|failed"
}

Process

1. Analyze

  • Validate agent availability
  • Check agent connectivity
  • Assess task complexity
  • Determine optimal distribution strategy

2. Plan

  • Select coordination approach
  • Define task allocation
  • Set execution order
  • Plan fallback mechanisms

3. Execute

  • Distribute tasks to agents
  • Monitor agent progress
  • Coordinate inter-agent communication
  • Aggregate results

4. Validate

  • Verify task completion
  • Check result consistency
  • Validate workflow integrity
  • Confirm agent satisfaction

Constraints

  • MUST NOT modify agent configurations without approval
  • MUST NOT exceed 120 seconds for complex workflows
  • MUST validate agent availability before distribution
  • MUST handle agent failures gracefully
  • MUST respect agent capacity limits

Environment Assumptions

  • OpenClaw agents operational and accessible
  • Agent communication channels available
  • Task queue system functional
  • Agent status monitoring active
  • Collaboration protocol established

Error Handling

  • Agent offline → Reassign task to available agent
  • Task timeout → Retry with different agent
  • Communication failure → Use fallback coordination
  • Agent capacity exceeded → Queue task for later execution

Example Usage Prompt

Orchestrate parallel analysis workflow across main and trading agents

Expected Output Example

{
  "summary": "Multi-agent workflow orchestrated successfully across 2 agents",
  "operation": "orchestrate",
  "agents_assigned": ["main", "trading"],
  "task_distribution": {
    "main": "Analyze blockchain state and transaction patterns",
    "trading": "Analyze marketplace pricing and order flow"
  },
  "workflow_status": "completed",
  "collaboration_results": {
    "main": {"status": "completed", "result": "analysis_complete"},
    "trading": {"status": "completed", "result": "analysis_complete"}
  },
  "issues": [],
  "recommendations": ["Consider adding GPU agent for compute-intensive analysis"],
  "confidence": 1.0,
  "execution_time": 45.2,
  "validation_status": "success"
}

Model Routing Suggestion

Reasoning Model (Claude Sonnet, GPT-4)

  • Complex workflow orchestration
  • Task distribution strategy
  • Agent capacity planning
  • Collaboration protocol management

Performance Notes

  • Execution Time: 10-60 seconds for distribution, 30-120 seconds for complex workflows
  • Memory Usage: <200MB for coordination operations
  • Network Requirements: Agent communication channels
  • Concurrency: Safe for multiple parallel workflows