override_completion
Set a participant's completion of an activity as a teacher does from the progress report (an override, shown as such). Takes the participant as get_completion_report gives them. Returns the state saved. Changes the participant's progress: confirm with the person first.
This record as markdown: /tools/falkenslab-moodle-mcp/override-completion.md
What override_completion does on Moodle
AI agents use override_completion to create or update resources in Moodle, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Moodle environment.
| Parameter | Type | Required | Description |
|---|---|---|---|
user | string | — | The participant's alias, as the reading tools give it when the server pseudonymizes |
state | string | Yes | |
userId | integer | — | The participant's user id, when the server shows names |
activityId | integer | Yes | The activity's id (course module id) |
Parameters from the server's own tool schema.
Why override_completion is rated Medium
An AI agent can call override_completion faster than any human can review: one bad instruction and it creates or modifies resources in Moodle by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
The rule that runs override_completion safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Moodle, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For override_completion, this is the rule to start with:
override_completion 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 Moodle, apply this rule, and every override_completion call is checked against it from then on.
Questions about override_completion
Set a participant's completion of an activity as a teacher does from the progress report (an override, shown as such). Takes the participant as get_completion_report gives them. Returns the state saved. Changes the participant's progress: confirm with the person first. It is categorised as a Write tool in the Moodle MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
override_completion accepts 4 parameters: user, state, userId, activityId. Required: state, activityId. The full parameter table on this page comes from the server's own tool schema.
Register the Moodle MCP server in PolicyLayer and add a rule for override_completion: 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 Moodle. Nothing to install.
override_completion 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 override_completion 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 override_completion. 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.
override_completion is provided by the Moodle MCP server (@falkenslab/moodle-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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