CoPaw Multi-Agent Collaboration

Problem It Solves

In multi-agent workflows, a single model often cannot cover decomposition, execution, review, and aggregation at the same time. Ad-hoc scripts that connect several models can become hard to manage: role boundaries blur, sessions interfere, permissions are scattered, and outputs are difficult to trace. The CoPaw multi-agent collaboration skill turns these interactions into a configurable set of CLI and API operations.

How It Works

Core capabilities include:
- Agent creation: create multiple agents with different roles, such as coordinator, executor, and reviewer.
- Trust configuration: define communication permissions and trust relationships between agents to reduce interference.
- Task routing: split complex work into subtasks and assign them to specific agents.
- Collaborative dialogue: manage multi-turn sessions across chain, parallel, hierarchical, and iterative patterns.
- Result aggregation: collect outputs from each agent and combine them into a final result.

The typical flow starts with environment discovery, then creates collaboration agents, writes role definition files, establishes inter-agent communication, and finally orchestrates the task flow. For sessions, use a unique session ID and include an identity prefix in messages so the exchange can be traced.

Boundaries and Notes

It is better suited to orchestration in local or controlled environments, not as a replacement for the underlying model capabilities. Watch permission isolation, workspace boundaries, communication audit, and resource quotas. Performance should be managed with LLM_MAX_CONCURRENT, LLM_MAX_QPM, caching, and batch processing. Debugging is easier when logs and daemon output are kept available.