operator_work_prune
Run operator-work.prune through the Appaloft application operation catalog. Shared with CLI and HTTP/API.
This record as markdown: /tools/appaloft-mcp/operator-work-prune.md
What operator_work_prune does on Appaloft
AI agents call operator_work_prune to permanently remove resources in Appaloft, typically in cleanup and lifecycle workflows. It does its job in a single call, and there is no undo.
| Parameter | Type | Required | Description |
|---|---|---|---|
before | string | Yes | |
dryRun | boolean | — | |
statuses | array | — |
Parameters from the server's own tool schema.
Why operator_work_prune is rated Critical
'Prune' operations typically remove/delete stale, old, or excess data irreversibly. Combined with sibling tools like 'audit_events_archives_prune' (which also prunes data) and 'account_delete', this server pattern confirms that 'prune' here means permanent deletion. The blast radius is high as it could remove operational work records across the system.
From the tool's definition 'prune' in the tool name and description — 'operator-work.prune' — indicates irreversible removal of operator work items or related data
Attacks that exploit this kind of access
The rule that runs operator_work_prune safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Appaloft, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For operator_work_prune, this is the rule to start with:
operator_work_prune is removed from the agent's tool list entirely, so the agent never calls it. The rest of the server keeps working.
The button opens the PolicyLayer dashboard: create your workspace, connect Appaloft, apply this rule, and every operator_work_prune call is checked against it from then on.
Questions about operator_work_prune
Run operator-work.prune through the Appaloft application operation catalog. Shared with CLI and HTTP/API. It is categorised as a Destructive tool in the Appaloft MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
operator_work_prune accepts 3 parameters: before, dryRun, statuses. Required: before. The full parameter table on this page comes from the server's own tool schema.
Register the Appaloft MCP server in PolicyLayer and add a rule for operator_work_prune: 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 Appaloft. Nothing to install.
operator_work_prune is a Destructive tool with critical risk. Critical-risk tools should be blocked by default and only enabled with explicit human approval.
Yes. Add a rate_limit block to the operator_work_prune 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 operator_work_prune. 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.
operator_work_prune is provided by the Appaloft MCP server (@appaloft/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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