edit_feedback_item

SERVERMoodle SOURCE@falkenslab/moodle-mcp

Medium RISK CLASS

Category Write

Parameters 122 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/falkenslab-moodle-mcp/edit-feedback-item.md

WHAT IT DOES

What edit_feedback_item does on Moodle

AI agents use edit_feedback_item 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
`info`	string	—
`label`	string	—
`range`	object	—	A numeric item's; a bound left out is none
`fields`	object	—	Any other field of the item's form, by name (itemsize, itemmaxlength…)
`itemId`	integer	Yes	The item's id, as get_feedback_items gives it
`display`	string	—	checkbox (several answers) for multichoice only
`options`	array	—	Choice items' options, in order; given, they replace them all
`contents`	string	—	A label's (HTML)
`question`	string	—	Every type but a label and a page break needs one
`required`	boolean	—
`dependsOn`	object	—	Show it only when another item was answered with this value: an item with a label, on an earlier page (a page break between them)
`feedbackId`	integer	Yes	The feedback's id (course module id), as get_course_structure gives it

Parameters from the server's own tool schema.

RISK

Why edit_feedback_item is rated Medium

An AI agent can call edit_feedback_item 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.

Risk signalsHigh parameter count (22 properties)

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs edit_feedback_item 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 edit_feedback_item, this is the rule to start with:

edit_feedback_item Rate-limited

edit_feedback_item 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": {
    "edit_feedback_item": {
      "limits": [
        {
          "counter": "edit_feedback_item_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Moodle, apply this rule, and every edit_feedback_item call is checked against it from then on.

FAQ

Questions about edit_feedback_item

What does the edit_feedback_item tool do? +

Change a feedback item with what is given: question, label, required, a choice's options (given, they replace them all) and settings, a numeric range, a label's contents, its dependency (removeDependency takes it away) and other fields. It keeps its type and place. Changes the course: 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.

What parameters does edit_feedback_item accept? +

edit_feedback_item accepts 12 parameters: info, label, range, fields, itemId, display, options, contents, question, required, dependsOn, feedbackId. Required: itemId, feedbackId. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on edit_feedback_item? +

Register the Moodle MCP server in PolicyLayer and add a rule for edit_feedback_item: 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.

What risk level is edit_feedback_item? +

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

Can I rate-limit edit_feedback_item? +

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

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

edit_feedback_item 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.

KEEP EXPLORING

More on Moodle, and thousands of servers like it.

This server

All 233 Moodle tools →

Across the catalogue

edit_screen on Stitch MCP Server → The MCP Attack Database →

Guides

Govern customer-ops agents →Argument validation →Scoped token →