face_check
FREE, before any paid render: does a picture or video contain a face, and which video models refuse it (they cannot take a real person
This record as markdown: /tools/hermoso/face-check.md
What face_check does on Hermoso
AI agents call face_check to retrieve information from Hermoso without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why face_check is rated Low
Even though face_check only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs face_check safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Hermoso, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For face_check, this is the rule to start with:
face_check is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Hermoso, apply this rule, and every face_check call is checked against it from then on.
Questions about face_check
FREE, before any paid render: does a picture or video contain a face, and which video models refuse it (they cannot take a real person. It is categorised as a Read tool in the Hermoso MCP Server, which means it retrieves data without modifying state.
Register the Hermoso MCP server in PolicyLayer and add a rule for face_check: 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 Hermoso. Nothing to install.
face_check is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the face_check 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 face_check. 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.
face_check is provided by the Hermoso MCP server (https://app.hermoso.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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