Audit a rendered mobile screen (iOS or Android) from a view-hierarchy/accessibility snapshot. Call with no arguments for the expected snapshot shape and how to capture it. Pass platform:"android" to score against the 48dp Material touch minimum and Material muted roles (onSurfaceVariant/outline =...
Risk signalsHigh parameter count (16 properties)
Part of the Raven server.
Free to start. No card required.
AI agents call audit_screen to retrieve information from Raven without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though audit_screen only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"audit_screen": {}
}
}See the full Raven policy for all 32 tools.
These attack patterns abuse exactly the kind of access audit_screen gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Audit a rendered mobile screen (iOS or Android) from a view-hierarchy/accessibility snapshot. Call with no arguments for the expected snapshot shape and how to capture it. Pass platform:"android" to score against the 48dp Material touch minimum and Material muted roles (onSurfaceVariant/outline = warn not fail); default platform:"ios" scores 44pt and treats secondaryLabel/tertiaryLabel as platform-standard. Both score touch targets, contrast, and visual rhythm (alignment, gap consistency, optical balance). Same return shape as audit_page.. It is categorised as a Read tool in the Raven MCP Server, which means it retrieves data without modifying state.
Register the Raven MCP server in PolicyLayer and add a rule for audit_screen: 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 Raven. Nothing to install.
audit_screen 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 audit_screen 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 audit_screen. 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.
audit_screen is provided by the Raven MCP server (raven-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 32 Raven tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
Free to start. No card required.
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