Submit feedback about PlanExe — issues, impressions, or suggestions. Callable at any point in the workflow; fire-and-forget, never blocks. Use category to classify: mcp (MCP tools, SSE, plan_status, workflow), plan (the generated output files), code (PlanExe source), docs (documentation), other. ...
Part of the PlanExe server.
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AI agents use send_feedback to create or modify resources in PlanExe. 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 send_feedback 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 PlanExe.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"send_feedback": {
"limits": [
{
"counter": "send_feedback_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full PlanExe policy for all 11 tools.
These attack patterns abuse exactly the kind of access send_feedback 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.
Submit feedback about PlanExe — issues, impressions, or suggestions. Callable at any point in the workflow; fire-and-forget, never blocks. Use category to classify: mcp (MCP tools, SSE, plan_status, workflow), plan (the generated output files), code (PlanExe source), docs (documentation), other. Optionally attach to a plan via plan_id. Use rating (1-5) for sentiment: 1=strong negative, 3=neutral, 5=strong positive. Especially useful for reporting: SSE streams that close before plan completion, plan_status returning stale or inconsistent data, queue delays where workers are slow to pick up plans, and impressions of plan output quality after reviewing reports. Include specific details (plan_id, percentages, timestamps) when reporting issues.. It is categorised as a Write tool in the PlanExe MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the PlanExe MCP server in PolicyLayer and add a rule for send_feedback: 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 PlanExe. Nothing to install.
send_feedback 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 send_feedback 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 send_feedback. 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.
send_feedback is provided by the PlanExe MCP server (https://mcp.planexe.org/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 11 PlanExe 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.