policy_evaluate

Evaluate an agent action against ADR-324 policy and persist a tamper-evident decision receipt. Use when a consequential tool, deployment, network, spend, or promotion action needs authorization.

SERVERClaude Flow SOURCEclaude-flow

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-ruvnet-claude-flow/policy-evaluate.md

WHAT IT DOES

What policy_evaluate does on Claude Flow

AI agents call policy_evaluate 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.

RISK

Why policy_evaluate is rated Low

Even though policy_evaluate only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs policy_evaluate 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 policy_evaluate, this is the rule to start with:

policy_evaluate Allowed

policy_evaluate is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "policy_evaluate": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Claude Flow, apply this rule, and every policy_evaluate call is checked against it from then on.

FAQ

Questions about policy_evaluate

What does the policy_evaluate tool do? +

Evaluate an agent action against ADR-324 policy and persist a tamper-evident decision receipt. Use when a consequential tool, deployment, network, spend, or promotion action needs authorization. It is categorised as a Read tool in the Claude Flow MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on policy_evaluate? +

Register the Claude Flow MCP server in PolicyLayer and add a rule for policy_evaluate: 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.

What risk level is policy_evaluate? +

policy_evaluate is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit policy_evaluate? +

Yes. Add a rate_limit block to the policy_evaluate 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 policy_evaluate completely? +

Set action: deny in the PolicyLayer policy for policy_evaluate. 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 policy_evaluate? +

policy_evaluate 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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