Medium Risk

hallucination_confidence_meter

Evaluates the likelihood of hallucination in LLM responses by comparing against HuggingFace model confidence scores. Designed for risk assessment personas to quantify response reliability. Accepts text snippets or model outputs, returns confidence metrics and potential hallucination warnings. Cro...

Part of the Mcp Knowledge server.

hallucination_confidence_meter can modify Mcp Knowledge data, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents use hallucination_confidence_meter to create or modify resources in Mcp Knowledge. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.

Without a policy, an AI agent could call hallucination_confidence_meter repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Mcp Knowledge.

Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "hallucination_confidence_meter": {
      "limits": [
        {
          "counter": "hallucination_confidence_meter_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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These attack patterns abuse exactly the kind of access hallucination_confidence_meter gives an agent. Each links to the full case and the policy that stops it:

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Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so hallucination_confidence_meter only ever does what you allow.

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Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the hallucination_confidence_meter tool do? +

Evaluates the likelihood of hallucination in LLM responses by comparing against HuggingFace model confidence scores. Designed for risk assessment personas to quantify response reliability. Accepts text snippets or model outputs, returns confidence metrics and potential hallucination warnings. Cross-references with top-performing models from the HuggingFace leaderboard.. It is categorised as a Write tool in the Mcp Knowledge MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on hallucination_confidence_meter? +

Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for hallucination_confidence_meter: 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 Mcp Knowledge. Nothing to install.

What risk level is hallucination_confidence_meter? +

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

Can I rate-limit hallucination_confidence_meter? +

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

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

hallucination_confidence_meter is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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