Select an option in a select/dropdown element. Returns full page representation after selection.
Part of the Charlotte server.
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AI agents use charlotte_select to create or modify resources in Charlotte. 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 charlotte_select 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 Charlotte.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"charlotte_select": {
"limits": [
{
"counter": "charlotte_select_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Charlotte policy for all 43 tools.
These attack patterns abuse exactly the kind of access charlotte_select 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.
Select an option in a select/dropdown element. Returns full page representation after selection.. It is categorised as a Write tool in the Charlotte MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Charlotte MCP server in PolicyLayer and add a rule for charlotte_select: 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 Charlotte. Nothing to install.
charlotte_select 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 charlotte_select 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 charlotte_select. 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.
charlotte_select is provided by the Charlotte MCP server (@ticktockbent/charlotte). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 43 Charlotte tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
4,600+ MCP servers and 31,000+ tools scanned and risk-classified.