hooks_model-outcome

Record model routing outcome for learning Use when native Bash hooks (via Claude Code\

SERVERClaude Flow SOURCEclaude-flow

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-ruvnet-claude-flow/hooks-model-outcome.md

WHAT IT DOES

What hooks_model-outcome does on Claude Flow

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

RISK

Why hooks_model-outcome is rated Medium

The tool records model routing outcomes, which is a write operation persisting data to some learning/feedback store. It has no apparent destructive, financial, or execution capabilities. Misuse could corrupt learning feedback loops or skew model routing decisions over time, warranting medium severity. Confidence is moderate because the description is brief and partially truncated.

From the tool's definition 'Record model routing outcome for learning' — the tool writes/records outcome data for a learning system

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs hooks_model-outcome 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 hooks_model-outcome, this is the rule to start with:

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.

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

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 Claude Flow 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 Claude Flow 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 Claude Flow. 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 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.

KEEP EXPLORING

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