log_rag_evaluation_feedback · SDOF Knowledge Base MCP

WHAT IT DOES

What log_rag_evaluation_feedback does on SDOF Knowledge Base

AI agents use log_rag_evaluation_feedback to create or update resources in SDOF Knowledge Base — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your SDOF Knowledge Base environment.

WHY IT NEEDS A POLICY

Why log_rag_evaluation_feedback needs a policy

This tool writes/creates feedback records for RAG evaluations. It is a write operation with no indication of deletion, execution, or financial impact. Misuse risk is low as it only logs evaluation feedback data.

From the tool's definition 'Logs feedback for a RAG evaluation' - logging/recording feedback data

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

log_rag_evaluation_feedback Rate-limited

log_rag_evaluation_feedback 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": {
    "log_rag_evaluation_feedback": {
      "limits": [
        {
          "counter": "log_rag_evaluation_feedback_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 SDOF Knowledge Base, so you can run agents against it safely.

FAQ

Questions about log_rag_evaluation_feedback

What does the log_rag_evaluation_feedback tool do? +

Logs feedback for a RAG evaluation. It is categorised as a Write tool in the SDOF Knowledge Base MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on log_rag_evaluation_feedback? +

Register the SDOF Knowledge Base MCP server in PolicyLayer and add a rule for log_rag_evaluation_feedback: 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 SDOF Knowledge Base. Nothing to install.

What risk level is log_rag_evaluation_feedback? +

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

Can I rate-limit log_rag_evaluation_feedback? +

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

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

log_rag_evaluation_feedback is provided by the SDOF Knowledge Base MCP server (tgf-between-your-legs/sdof-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.