STEP 3: Submit a question or topic request. ALWAYS call this when query_knowledge returned no results. Popular suggestions are prioritized for new knowledge unit creation.
AI agents call suggest_question to retrieve information from Knowledgelib without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool is purely informational and passive—it collects user input to inform future content creation priorities, similar to a survey or feedback submission. It does not read sensitive data beyond what the user explicitly provides, does not modify or delete anything, does not execute code, and does not involve financial transactions.
From the tool's definition The tool 'suggest_question' submits a question or topic request for prioritization in knowledge unit creation.
Attacks that exploit this kind of access
STEP 3: Submit a question or topic request. ALWAYS call this when query_knowledge returned no results. Popular suggestions are prioritized for new knowledge unit creation. It is categorised as a Read tool in the Knowledgelib MCP Server, which means it retrieves data without modifying state.
Register the Knowledgelib MCP server in PolicyLayer and add a rule for suggest_question: 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 Knowledgelib. Nothing to install.
suggest_question is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the suggest_question 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.
Set action: deny in the PolicyLayer policy for suggest_question. 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.
suggest_question is provided by the Knowledgelib MCP server (peterbeck111/knowledgelib-io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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