Restore rows from a snapshot into a Knowledge Data list without wiping computed fields. Modes (computed fields like scores and enrichment are always preserved): - "merge-restore" (default) — for rows that already exist: shallow-merges snapshot fields back in (existing computed fields survive; sna...
Part of the Agentled server.
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AI agents use restore_knowledge_list_snapshot to create or modify resources in Agentled. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call restore_knowledge_list_snapshot repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Agentled.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"restore_knowledge_list_snapshot": {
"limits": [
{
"counter": "restore_knowledge_list_snapshot_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Agentled policy for all 119 tools.
These attack patterns abuse exactly the kind of access restore_knowledge_list_snapshot gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Restore rows from a snapshot into a Knowledge Data list without wiping computed fields. Modes (computed fields like scores and enrichment are always preserved): - "merge-restore" (default) — for rows that already exist: shallow-merges snapshot fields back in (existing computed fields survive; snapshot fields win on conflict). New rows are inserted. Use this as the rollback path — it undoes a bad migration without destroying downstream work. - "append" — inserts only rows not already present; never touches existing rows. Use this when restoring into a new list or when you want to add missing rows without altering anything. The target listKey may differ from the snapshot's source listKey — this enables cross-list cloning. If the target list doesn't exist it will be auto-created using the snapshot's schema. Returns: { restored (new rows inserted), merged (existing rows updated), skipped, errors[] }.. It is categorised as a Write tool in the Agentled MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Agentled MCP server in PolicyLayer and add a rule for restore_knowledge_list_snapshot: 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.
restore_knowledge_list_snapshot 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 restore_knowledge_list_snapshot 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 restore_knowledge_list_snapshot. 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.
restore_knowledge_list_snapshot 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 119 Agentled tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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