Delete specific rows from a knowledge list by their IDs. This action is irreversible. For more than 10 rows the API requires confirm: true — this tool sends it automatically. Returns: { deleted, errors[] } where each error includes a structured code field: - foreign_key_constraint: row is referen...
Part of the Agentled server.
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AI agents may call delete_knowledge_rows to permanently remove or destroy resources in Agentled. Without a policy, an autonomous agent could delete critical data in a loop with no way to undo the damage. PolicyLayer blocks destructive tools by default and requires explicit human approval before enabling them.
Without a policy, an AI agent could call delete_knowledge_rows in a loop, permanently destroying resources in Agentled. There is no undo for destructive operations. PolicyLayer blocks this tool by default and only allows it when a human explicitly approves the action.
Destructive tools permanently remove data. Block by default. Only enable with explicit approval workflows.
{
"version": "1",
"default": "deny",
"hide": [
"delete_knowledge_rows"
]
}See the full Agentled policy for all 102 tools.
These attack patterns abuse exactly the kind of access delete_knowledge_rows gives an agent. Each links to the full case and the policy that stops it:
Other destructive tools across the catalogue. The same approach applies to each: deny by default, or require human approval.
Delete specific rows from a knowledge list by their IDs. This action is irreversible. For more than 10 rows the API requires confirm: true — this tool sends it automatically. Returns: { deleted, errors[] } where each error includes a structured code field: - foreign_key_constraint: row is referenced by KG edges (scoring predictions, outcomes, relations) and cannot be hard-deleted - not_found: row ID does not exist - permission_denied: insufficient workspace permissions - delete_failed: unclassified failure IMPORTANT: Rows referenced by KG edges cannot be hard-deleted. If you receive foreign_key_constraint errors, use soft-delete instead: call upsert_knowledge_rows with mergeStrategy "merge" and rowData { _dropped: true, _dropReason: "..." }. Workflow readers typically filter on _dropped or status != "noise", so soft-deleted rows are excluded from downstream reads.. It is categorised as a Destructive tool in the Agentled MCP Server, which means it can permanently delete or destroy data. Block by default and require explicit approval.
Register the Agentled MCP server in PolicyLayer and add a rule for delete_knowledge_rows: 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 Agentled. Nothing to install.
delete_knowledge_rows 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 delete_knowledge_rows 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 delete_knowledge_rows. 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.
delete_knowledge_rows is provided by the Agentled MCP server (@agentled/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 102 Agentled tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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