Propose or vote on consensus with BFT, Raft, or Quorum strategies Use when native Task is wrong because you need queen-led collective intelligence — Byzantine-FT consensus, broadcast across many worker agents, shared memory with bounded conflict. For a single subagent, native Task is fine. Pair w...
AI agents invoke hive-mind_consensus to trigger actions in Claude Flow. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool triggers distributed consensus operations across multiple agents using BFT/Raft/Quorum protocols. It orchestrates external agent coordination and communication — broadcasting to worker agents and managing shared memory state. This is an Execute-category action because it runs multi-agent coordination logic with side effects dependent on arguments (topology, strategy, proposals).
From the tool's definition Propose or vote on consensus with BFT, Raft, or Quorum strategies... broadcast across many worker agents, shared memory with bounded conflict
Attacks that exploit this kind of access
Propose or vote on consensus with BFT, Raft, or Quorum strategies Use when native Task is wrong because you need queen-led collective intelligence — Byzantine-FT consensus, broadcast across many worker agents, shared memory with bounded conflict. For a single subagent, native Task is fine. Pair with swarm_init first to set topology. It is categorised as a Execute tool in the Claude Flow MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Claude Flow MCP server in PolicyLayer and add a rule for hive-mind_consensus: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Claude Flow. Nothing to install.
hive-mind_consensus is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the hive-mind_consensus rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for hive-mind_consensus. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
hive-mind_consensus is provided by the Claude Flow MCP server (claude-flow). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.