coordination_load_balance
Configure load balancing Use when native Task is wrong because the work crosses multiple agents that need to vote/sync/load-balance — TodoWrite + a single Task cannot orchestrate consensus. For one-off subtask dispatch, native Task is fine.
This record as markdown: /tools/ruflo/coordination-load-balance.md
What coordination_load_balance does on Ruflo
AI agents invoke coordination_load_balance 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 coordination_load_balance is rated High
This tool configures and triggers load balancing behavior across multiple autonomous agents, involving consensus/voting/sync operations. It's not merely reading state or writing a config record — it actively orchestrates agent workflows and dispatches work. This falls under Execute due to triggering external multi-agent operations whose effects depend on arguments.
From the tool's definition 'Configure load balancing' across 'multiple agents that need to vote/sync/load-balance' — triggers active coordination and orchestration across autonomous agent swarms
Attacks that exploit this kind of access
The rule that runs coordination_load_balance safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Ruflo, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For coordination_load_balance, this is the rule to start with:
coordination_load_balance 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Ruflo, apply this rule, and every coordination_load_balance call is checked against it from then on.
Questions about coordination_load_balance
Configure load balancing Use when native Task is wrong because the work crosses multiple agents that need to vote/sync/load-balance — TodoWrite + a single Task cannot orchestrate consensus. For one-off subtask dispatch, native Task is fine. 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.
Register the Ruflo MCP server in PolicyLayer and add a rule for coordination_load_balance: 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.
coordination_load_balance 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 coordination_load_balance 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 coordination_load_balance. 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.
coordination_load_balance 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.
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