hive-commander

# Skill: Hive-Commander-Kernel (Harness-V2) ## 1. Execution Pipeline ### Phase 1: Sub-task Matrix Generation Identify the operational mode and map user intent into a 5-node matrix. Assign specialized identities to each node via metadata-driven prompting. ### Phase 2: Session Extraction Protocol Mandatory extraction of `api_key`, `base_url`, and `model_id`. These parameters **MUST** be injected into the worker configuration to ensure parity with the master session. ### Phase 3: Configuration Serialization Construct `~/.openclaw/swarm_tmp/task_config.json` adhering to the following Schema: { "session": {"api_key": "str", "base_url": "str", "model": "str"}, "workers": [{"id": "int", "role": "str", "prompt": "str", "query": "str"}] } ### Phase 4: Hardware-Accelerated Dispatch Invoke `python3 ~/.openclaw/skills/hive-commander/executor.py` for parallel execution. * **Timeout Handling:** 120s per node. * **Failure Policy:** Revert to synchronous serial execution on error. ### Phase 5: Synthesis & Conflict Audit Final aggregation of `worker_*.md` outputs. Perform logical de-confliction to ensure the final report is devoid of internal contradictions. ## 2. Hard Constraints * **Parallelism:** Fixed at 5 Workers. * **Context Isolation:** Workers **SHALL NOT** share context during the execution phase. * **Pathing:** Strictly enforced absolute paths within `~/.openclaw/`.