Submit structured outcome feedback for a previous scoring event so Sentinel can track real-world claims results.
Part of the Scoring server.
Free to start. No card required.
AI agents use submit_feedback to create or modify resources in Scoring. 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 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 Scoring.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"submit_feedback": {
"limits": [
{
"counter": "submit_feedback_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Scoring policy for all 8 tools.
These attack patterns abuse exactly the kind of access submit_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 structured outcome feedback for a previous scoring event so Sentinel can track real-world claims results.. It is categorised as a Write tool in the Scoring MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Scoring MCP server in PolicyLayer and add a rule for submit_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 Scoring. Nothing to install.
submit_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 submit_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 submit_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.
submit_feedback is provided by the Scoring MCP server (https://mcp.sentinelsignal.io/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 8 Scoring 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.