get_proactive_alerts
Scan causal memory for watchlist-worthy alerts: new events on tracked entities, unresolved important changes, stale packets, trajectory drift, and repeated unanswered queries. Returns prioritized alerts with suggested actions.
This record as markdown: /tools/io-github-homenshum-nodebench/get-proactive-alerts.md
What get_proactive_alerts does on Nodebench
AI agents call get_proactive_alerts to retrieve information from Nodebench without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why get_proactive_alerts is rated Low
This tool queries internal state (causal memory/watchlist) and returns alert data. While it monitors for events and suggests actions, it does not execute those actions, modify data, delete anything, or move money. The output is informational alerts intended to inform decision-making, not trigger autonomous operations. This is a classic monitoring/alerting tool in the Read category.
From the tool's definition Tool description: 'Scan causal memory for watchlist-worthy alerts...Returns prioritized alerts with suggested actions.' The verbs 'scan' and 'returns' indicate data retrieval with no modification or execution of external operations.
Attacks that exploit this kind of access
The rule that runs get_proactive_alerts safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Nodebench, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_proactive_alerts, this is the rule to start with:
get_proactive_alerts is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Nodebench, apply this rule, and every get_proactive_alerts call is checked against it from then on.
Questions about get_proactive_alerts
Scan causal memory for watchlist-worthy alerts: new events on tracked entities, unresolved important changes, stale packets, trajectory drift, and repeated unanswered queries. Returns prioritized alerts with suggested actions. It is categorised as a Read tool in the Nodebench MCP Server, which means it retrieves data without modifying state.
Register the Nodebench MCP server in PolicyLayer and add a rule for get_proactive_alerts: 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 Nodebench. Nothing to install.
get_proactive_alerts 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 get_proactive_alerts 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 get_proactive_alerts. 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.
get_proactive_alerts is provided by the Nodebench MCP server (nodebench-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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