list_feedback

Read what the OWNER said went wrong (#514) — in-session complaints about an agent, each anchored to the turn it is about. Every row carries

SERVERProAgentStore SOURCEhttps://mcp.proagentstore.online/mcp

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade D, identity unverified Pull the record →

This record as markdown: /tools/io-github-proagentstore-platform/list-feedback.md

WHAT IT DOES

What list_feedback does on ProAgentStore

AI agents call list_feedback to retrieve information from ProAgentStore without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why list_feedback is rated Low

Retrieves feedback data without modification or external side effects; purely informational query.

From the tool's definition Read what the OWNER said went wrong, in-session complaints about an agent

Risk signalsBulk/mass operation — affects multiple targets

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs list_feedback safely

PolicyLayer is an MCP gateway: it sits between your AI agents and ProAgentStore, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For list_feedback, this is the rule to start with:

list_feedback Allowed

list_feedback is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "list_feedback": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect ProAgentStore, apply this rule, and every list_feedback call is checked against it from then on.

FAQ

Questions about list_feedback

What does the list_feedback tool do? +

Read what the OWNER said went wrong (#514) — in-session complaints about an agent, each anchored to the turn it is about. Every row carries. It is categorised as a Read tool in the ProAgentStore MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on list_feedback? +

Register the ProAgentStore MCP server in PolicyLayer and add a rule for list_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 ProAgentStore. Nothing to install.

What risk level is list_feedback? +

list_feedback is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit list_feedback? +

Yes. Add a rate_limit block to the list_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 list_feedback completely? +

Set action: deny in the PolicyLayer policy for list_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 list_feedback? +

list_feedback is provided by the ProAgentStore MCP server (https://mcp.proagentstore.online/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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