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.
This record as markdown: /tools/ruflo/policy-evaluate.md
What policy_evaluate does on Ruflo
AI agents invoke policy_evaluate 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 policy_evaluate is rated High
Triggers policy evaluation and persists authorization receipts, executing external compliance operations.
From the tool's definition evaluate agent action against policy, persist tamper-evident decision receipt
Attacks that exploit this kind of access
The rule that runs policy_evaluate 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 policy_evaluate, this is the rule to start with:
policy_evaluate 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 policy_evaluate call is checked against it from then on.
Questions about 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. 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 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 Ruflo. Nothing to install.
policy_evaluate 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 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.
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.
policy_evaluate 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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