hive-mind_consensus · Ruflo MCP: Risk & Policy

WHAT IT DOES

What hive-mind_consensus does on Ruflo

AI agents invoke hive-mind_consensus to trigger actions in Ruflo. 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.

WHY IT NEEDS A POLICY

Why hive-mind_consensus needs a policy

This tool triggers distributed consensus operations across multiple autonomous agents — proposing/voting mechanisms that coordinate and direct swarm behavior. It executes cross-agent coordination workflows (BFT/Raft/Quorum) that can propagate decisions broadly across the agent pool.

From the tool's definition 'Propose or vote on consensus with BFT, Raft, or Quorum strategies', 'Byzantine-FT consensus, broadcast across many worker agents, shared memory with bounded conflict', 'queen-led collective intelligence'

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

hive-mind_consensus Rate-limited

hive-mind_consensus stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "hive-mind_consensus": {
      "limits": [
        {
          "counter": "hive-mind_consensus_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Ruflo, so you can run agents against it safely.

FAQ

Questions about hive-mind_consensus

What does the hive-mind_consensus tool do? +

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 Ruflo MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on hive-mind_consensus? +

Register the Ruflo 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 Ruflo. Nothing to install.

What risk level is hive-mind_consensus? +

hive-mind_consensus is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit hive-mind_consensus? +

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.

How do I block hive-mind_consensus completely? +

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.

What MCP server provides hive-mind_consensus? +

hive-mind_consensus is provided by the Ruflo MCP server (ruvnet/ruflo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.