Report a bug, request a feature, escalate an issue, or ask the Agentled team a question. Use this when you encounter something broken, have a suggestion for improvement, need human help from the Agentled team, or want to escalate a problem you cannot solve. Include a clear title and detailed desc...
Part of the Agentled server.
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AI agents use submit_feedback_to_agentled 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 submit_feedback_to_agentled 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": {
"submit_feedback_to_agentled": {
"limits": [
{
"counter": "submit_feedback_to_agentled_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 submit_feedback_to_agentled 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.
Report a bug, request a feature, escalate an issue, or ask the Agentled team a question. Use this when you encounter something broken, have a suggestion for improvement, need human help from the Agentled team, or want to escalate a problem you cannot solve. Include a clear title and detailed description. Provide the user's email if follow-up is needed.. 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 submit_feedback_to_agentled: 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.
submit_feedback_to_agentled 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 submit_feedback_to_agentled 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 submit_feedback_to_agentled. 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.
submit_feedback_to_agentled 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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