Medium Risk

submit_retrieval_feedback

Provide feedback on memory retrieval quality for learning

Part of the Vasperamemory server.

submit_retrieval_feedback can modify Vasperamemory 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 submit_retrieval_feedback to create or modify resources in Vasperamemory. 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 submit_retrieval_feedback 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 Vasperamemory.

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

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

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These attack patterns abuse exactly the kind of access submit_retrieval_feedback 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 submit_retrieval_feedback 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 submit_retrieval_feedback tool do? +

Provide feedback on memory retrieval quality for learning. It is categorised as a Write tool in the Vasperamemory MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on submit_retrieval_feedback? +

Register the Vasperamemory MCP server in PolicyLayer and add a rule for submit_retrieval_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 Vasperamemory. Nothing to install.

What risk level is submit_retrieval_feedback? +

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

Can I rate-limit submit_retrieval_feedback? +

Yes. Add a rate_limit block to the submit_retrieval_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 submit_retrieval_feedback completely? +

Set action: deny in the PolicyLayer policy for submit_retrieval_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 submit_retrieval_feedback? +

submit_retrieval_feedback is provided by the Vasperamemory MCP server (vasperamemory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Vasperamemory tool call.

Deterministic rules across all 48 Vasperamemory tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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