Low Risk

preflight_should_i_act

The single call an agent makes before transacting with a destination on the open web. Composes the cross-lens verdict with a bounded Tracker-presence bonus, maps the adjusted trust score to a tri-state decision (allow / caution / deny), and returns a 5-minute signed consultation receipt (sigil_to...

Part of the TunnelMind Data API server.

preflight_should_i_act is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

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AI agents call preflight_should_i_act to retrieve information from TunnelMind Data API 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 preflight_should_i_act 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.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "preflight_should_i_act": {}
  }
}

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These attack patterns abuse exactly the kind of access preflight_should_i_act 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 preflight_should_i_act only ever does what you allow.

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Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the preflight_should_i_act tool do? +

The single call an agent makes before transacting with a destination on the open web. Composes the cross-lens verdict with a bounded Tracker-presence bonus, maps the adjusted trust score to a tri-state decision (allow / caution / deny), and returns a 5-minute signed consultation receipt (sigil_token with sub: preflight:consulted). The receipt is the load-bearing artifact: the agent attaches it to its action log as cryptographic proof that the destination was consulted before action. The decision itself is commodity-shaped; the *receipt of having asked* is what accountability requires. When ait is supplied, the consultation additionally chains a witness-tier preflight:consulted event onto the ATAP AIT, signed by OAI-2026-0000201 — turning the consultation into a hash-chained, replayable artifact. Tracker presence applies a bounded +0.05 trust bonus before decision mapping (capped at 1.0). Absence is never a penalty — most of the open web is not in the tracker corpus and that's expected. Defaults: allow >= 0.70, caution >= 0.40, else deny. Thresholds are overridable per request; weights are inherited from cross_lens_verify.. It is categorised as a Read tool in the TunnelMind Data API MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on preflight_should_i_act? +

Register the TunnelMind Data API MCP server in PolicyLayer and add a rule for preflight_should_i_act: 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 TunnelMind Data API. Nothing to install.

What risk level is preflight_should_i_act? +

preflight_should_i_act is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit preflight_should_i_act? +

Yes. Add a rate_limit block to the preflight_should_i_act 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 preflight_should_i_act completely? +

Set action: deny in the PolicyLayer policy for preflight_should_i_act. 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 preflight_should_i_act? +

preflight_should_i_act is provided by the TunnelMind Data API MCP server (https://mcp-data.tunnelmind.ai/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every TunnelMind Data API tool call.

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