kg_suggest_sample_questions
Suggest up to six sample questions to ask the knowledge graph: three standard ones built around the most-mentioned entities, and up to three drawn from the main topics of the content. Optionally for one project.
This record as markdown: /tools/io-stablebaseline-sb/kg-suggest-sample-questions.md
What kg_suggest_sample_questions does on Stable Baseline
AI agents use kg_suggest_sample_questions to create or update resources in Stable Baseline, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Stable Baseline environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
projectId | string | — |
Parameters from the server's own tool schema.
Why kg_suggest_sample_questions is rated Medium
An AI agent can call kg_suggest_sample_questions faster than any human can review: one bad instruction and it creates or modifies resources in Stable Baseline by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs kg_suggest_sample_questions safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Stable Baseline, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For kg_suggest_sample_questions, this is the rule to start with:
kg_suggest_sample_questions 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Stable Baseline, apply this rule, and every kg_suggest_sample_questions call is checked against it from then on.
Questions about kg_suggest_sample_questions
Suggest up to six sample questions to ask the knowledge graph: three standard ones built around the most-mentioned entities, and up to three drawn from the main topics of the content. Optionally for one project. It is categorised as a Write tool in the Stable Baseline MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
kg_suggest_sample_questions accepts 1 parameter: projectId. The full parameter table on this page comes from the server's own tool schema.
Register the Stable Baseline MCP server in PolicyLayer and add a rule for kg_suggest_sample_questions: 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 Stable Baseline. Nothing to install.
kg_suggest_sample_questions is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the kg_suggest_sample_questions 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 kg_suggest_sample_questions. 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.
kg_suggest_sample_questions is provided by the Stable Baseline MCP server (https://api.stablebaseline.io/functions/v1/cloud-serve/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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