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browser_performance_audit

browser_performance_audit

Part of the Looking Glass server.

browser_performance_audit can trigger actions in Looking Glass, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke browser_performance_audit to trigger processes or run actions in Looking Glass. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

browser_performance_audit can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "browser_performance_audit": {
      "limits": [
        {
          "counter": "browser_performance_audit_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Looking Glass policy for all 71 tools.

Get this rule live on your own Looking Glass server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access browser_performance_audit gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so browser_performance_audit only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the browser_performance_audit tool do? +

browser_performance_audit. It is categorised as a Execute tool in the Looking Glass MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on browser_performance_audit? +

Register the Looking Glass MCP server in PolicyLayer and add a rule for browser_performance_audit: 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 Looking Glass. Nothing to install.

What risk level is browser_performance_audit? +

browser_performance_audit is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit browser_performance_audit? +

Yes. Add a rate_limit block to the browser_performance_audit 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.

How do I block browser_performance_audit completely? +

Set action: deny in the PolicyLayer policy for browser_performance_audit. 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.

What MCP server provides browser_performance_audit? +

browser_performance_audit is provided by the Looking Glass MCP server (looking-glass-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Looking Glass tool call.

Deterministic rules across all 71 Looking Glass tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

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