update_requisition · Kula Ai MCP: Risk & Policy

WHAT IT DOES

What update_requisition does on Kula Ai

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

WHY IT NEEDS A POLICY

Why update_requisition needs a policy

This is a Write operation because it modifies existing recruiting data (requisitions) in a reversible manner. Severity is high because requisition updates in a recruiting system can affect job postings, hiring workflows, and candidate pipeline management across an organization.

From the tool's definition Tool description states 'Update an existing requisition' which modifies data. Constraint language 'Pass all custom field values in additional_info — omitted fields will be cleared' indicates the operation can overwrite or clear fields, creating reversible but…

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_requisition Rate-limited

update_requisition 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": {
    "update_requisition": {
      "limits": [
        {
          "counter": "update_requisition_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 Kula Ai, so you can run agents against it safely.

FAQ

Questions about update_requisition

What does the update_requisition tool do? +

Update an existing requisition. Cannot modify requisitions with closed, archived, or filled statuses. Pass all custom field values in additional_info — omitted fields will be cleared. It is categorised as a Write tool in the Kula Ai MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_requisition? +

Register the Kula Ai MCP server in PolicyLayer and add a rule for update_requisition: 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 Kula Ai. Nothing to install.

What risk level is update_requisition? +

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

Can I rate-limit update_requisition? +

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

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

update_requisition is provided by the Kula Ai MCP server (kula-ai/kula-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.