hooks_model-outcome · Ruflo MCP: Risk & Policy

WHAT IT DOES

What hooks_model-outcome does on Ruflo

AI agents use hooks_model-outcome to create or update resources in Ruflo — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Ruflo environment.

WHY IT NEEDS A POLICY

Why hooks_model-outcome needs a policy

The tool records (writes) model routing outcomes, which modifies stored learning/training data. This is a Write operation as it creates or updates persistent records. It does not execute code, delete data, or involve financial transactions. Severity is medium because misuse could corrupt the swarm's self-learning routing decisions, degrading agent coordination across the system.

From the tool's definition 'Record model routing outcome for learning' — the tool writes/persists outcome data to support adaptive learning

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

hooks_model-outcome Rate-limited

hooks_model-outcome stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "hooks_model-outcome": {
      "limits": [
        {
          "counter": "hooks_model-outcome_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Ruflo, so you can run agents against it safely.

FAQ

Questions about hooks_model-outcome

What does the hooks_model-outcome tool do? +

Record model routing outcome for learning Use when native Bash hooks (via Claude Code\. It is categorised as a Write tool in the Ruflo MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on hooks_model-outcome? +

Register the Ruflo MCP server in PolicyLayer and add a rule for hooks_model-outcome: 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.

What risk level is hooks_model-outcome? +

hooks_model-outcome is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit hooks_model-outcome? +

Yes. Add a rate_limit block to the hooks_model-outcome 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 hooks_model-outcome completely? +

Set action: deny in the PolicyLayer policy for hooks_model-outcome. 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 hooks_model-outcome? +

hooks_model-outcome 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.