This record as markdown: /tools/kh0pper-crow/maker-update-learner.md
What maker_update_learner does on Crow
AI agents use maker_update_learner to create or update resources in Crow, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Crow environment.
Why maker_update_learner is rated Medium
This tool creates or modifies data reversibly by updating learner information. While the exact scope and impact are not fully detailed in the description, updating learner records in a project management system typically affects user profiles or learning progress data. This is reversible (data can be updated again or rolled back) and does not delete data or execute arbitrary code, placing it in the Write category.
From the tool's definition Tool name 'maker_update_learner' and description 'Update a learner' indicate modification of existing data. The verb 'update' is a write operation that changes learner records.
Attacks that exploit this kind of access
The rule that runs maker_update_learner safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Crow, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For maker_update_learner, this is the rule to start with:
maker_update_learner 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 Crow, apply this rule, and every maker_update_learner call is checked against it from then on.
Questions about maker_update_learner
Update a learner. It is categorised as a Write tool in the Crow MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Crow MCP server in PolicyLayer and add a rule for maker_update_learner: 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 Crow. Nothing to install.
maker_update_learner 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 maker_update_learner 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 maker_update_learner. 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.
maker_update_learner is provided by the Crow MCP server (kh0pper/crow). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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