trigger_learning · Session Buddy MCP: Risk & Policy

WHAT IT DOES

What trigger_learning does on Session Buddy

AI agents invoke trigger_learning to trigger actions in Session Buddy. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why trigger_learning needs a policy

This tool executes a learning operation triggered by the user, which processes checkpoint data to extract and store learnings. While not destructive or financial, it performs a computational/operational action (learning extraction) that modifies the internal state of the session memory system. The phrase 'trigger' indicates active invocation of a procedure.

From the tool's definition Manually trigger learning from a checkpoint.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

trigger_learning Rate-limited

trigger_learning stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "trigger_learning": {
      "limits": [
        {
          "counter": "trigger_learning_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Session Buddy, so you can run agents against it safely.

FAQ

Questions about trigger_learning

What does the trigger_learning tool do? +

Manually trigger learning from a checkpoint. It is categorised as a Execute tool in the Session Buddy MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on trigger_learning? +

Register the Session Buddy MCP server in PolicyLayer and add a rule for trigger_learning: 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 Session Buddy. Nothing to install.

What risk level is trigger_learning? +

trigger_learning is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit trigger_learning? +

Yes. Add a rate_limit block to the trigger_learning 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 trigger_learning completely? +

Set action: deny in the PolicyLayer policy for trigger_learning. 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 trigger_learning? +

trigger_learning is provided by the Session Buddy MCP server (lesleslie/session-buddy). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.