agent_health
Report measured agent_execute provider-call outcomes over the last 20 calls: API success-ratio health (0-1), error rate, and response-latency p50/p95. This does not measure task correctness. Agents with no observed calls have unknown health; registration is not proof of a running process. Native ...
This record as markdown: /tools/io-github-ruvnet-claude-flow/agent-health.md
What agent_health does on Claude Flow
AI agents call agent_health to retrieve information from Claude Flow without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why agent_health is rated Low
Retrieves historical metrics and health status data with no side effects or modifications.
From the tool's definition Report measured outcomes, API success-ratio health, error rate, response-latency. Does not measure task correctness.
Attacks that exploit this kind of access
The rule that runs agent_health safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Claude Flow, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For agent_health, this is the rule to start with:
agent_health 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 Claude Flow, apply this rule, and every agent_health call is checked against it from then on.
Questions about agent_health
Report measured agent_execute provider-call outcomes over the last 20 calls: API success-ratio health (0-1), error rate, and response-latency p50/p95. This does not measure task correctness. Agents with no observed calls have unknown health; registration is not proof of a running process. Native Task and hooks_post-task outcomes are not recorded here. Use when you need measured reliability for agents driven through agent_execute; native Task results are invisible to this tool, so inspect those directly. It is categorised as a Read tool in the Claude Flow MCP Server, which means it retrieves data without modifying state.
Register the Claude Flow MCP server in PolicyLayer and add a rule for agent_health: 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.
agent_health 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_health 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_health. 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_health 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.
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