reflect_outcome · Decision State MCP: Risk & Policy

WHAT IT DOES

What reflect_outcome does on Decision State MCP

AI agents use reflect_outcome to create or update resources in Decision State MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Decision State MCP environment.

WHY IT NEEDS A POLICY

Why reflect_outcome needs a policy

This tool writes outcome data associated with a prior decision into the state store. It is a Write operation (creating a new record), not Destructive (no deletion), not Execute (no code runs), and not Financial. Severity is low because it only appends reflective metadata about past decisions; misuse has minimal blast radius.

From the tool's definition 'Record the outcome of a previous decision or implementation' — creates/stores new outcome data

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

reflect_outcome Rate-limited

reflect_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": {
    "reflect_outcome": {
      "limits": [
        {
          "counter": "reflect_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 Decision State MCP, so you can run agents against it safely.

FAQ

Questions about reflect_outcome

What does the reflect_outcome tool do? +

Record the outcome of a previous decision or implementation. It is categorised as a Write tool in the Decision State MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on reflect_outcome? +

Register the Decision State MCP server in PolicyLayer and add a rule for reflect_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 Decision State MCP. Nothing to install.

What risk level is reflect_outcome? +

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

Can I rate-limit reflect_outcome? +

Yes. Add a rate_limit block to the reflect_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 reflect_outcome completely? +

Set action: deny in the PolicyLayer policy for reflect_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 reflect_outcome? +

reflect_outcome is provided by the Decision State MCP server (koolercat/mcp-state). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.