This record as markdown: /tools/ruflo/agent-status.md
What agent_status does on Ruflo
AI agents call agent_status to retrieve information from Ruflo without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why agent_status is rated Low
This tool retrieves status information about subagents, which is a read-only operation with no side effects. It fits the Read category (get, fetch) as it queries the state of agents without creating, modifying, deleting, or executing operations. The blast radius of misuse is minimal—an agent could gather information about other agents but cannot cause harm through this operation alone.
From the tool's definition Tool name 'agent_status' and description 'Get subagent status' indicate a query operation that retrieves status information about agents without modifying, executing, or deleting any data.
Attacks that exploit this kind of access
The rule that runs agent_status 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 agent_status, this is the rule to start with:
agent_status is read-only, so it stays allowed. 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 agent_status call is checked against it from then on.
Questions about agent_status
Get subagent status. It is categorised as a Read tool in the Ruflo MCP Server, which means it retrieves data without modifying state.
Register the Ruflo MCP server in PolicyLayer and add a rule for agent_status: 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.
agent_status is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the agent_status 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 agent_status. 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.
agent_status 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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