promote_learning · Anchor MCP: Risk & Policy

WHAT IT DOES

What promote_learning does on Anchor

AI agents use promote_learning to create or update resources in Anchor — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Anchor environment.

WHY IT NEEDS A POLICY

Why promote_learning needs a policy

The tool creates or modifies data (appending to rules.md) in a reversible manner. While file modifications can affect project behavior, appending is not destructive (the original content remains intact and can be edited or removed). This qualifies as Write rather than Execute or Destructive.

From the tool's definition Tool description states it 'Appends plan learnings to rules.md' — this modifies a file by adding content to it.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

promote_learning Rate-limited

promote_learning 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "promote_learning": {
      "limits": [
        {
          "counter": "promote_learning_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

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

FAQ

Questions about promote_learning

What does the promote_learning tool do? +

Promote learnings from a plan into project rules. Appends plan learnings to rules.md. It is categorised as a Write tool in the Anchor MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on promote_learning? +

Register the Anchor MCP server in PolicyLayer and add a rule for promote_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 Anchor. Nothing to install.

What risk level is promote_learning? +

promote_learning is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit promote_learning? +

Yes. Add a rate_limit block to the promote_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 promote_learning completely? +

Set action: deny in the PolicyLayer policy for promote_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 promote_learning? +

promote_learning is provided by the Anchor MCP server (thewillmoss/anchor-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.