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OT Intel API

AI/Agentic Copilot Attack Surface Lookup

getAiExposure
Read-only

AI/agentic copilot exposure lookup for OT/ICS vendors. Returns the vendor's documented AI/agentic copilot, autonomy level (advisory vs agentic — the key risk differentiator), access, and applicable MITRE ATLAS techniques. Hand-verified mapping, ATLAS IDs confirmed against the live atlas.mitre.org matrix. Deterministic, no LLM in the lookup path. Price: $0.20 USDC per call via x402 on Base mainnet. An unpaid call returns an x402 PaymentRequired challenge; retry the identical call with the signed payload in _meta["x402/payment"].

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
vendorYesOT/ICS vendor name e.g. Siemens, Schneider Electric, Rockwell Automation, ABB, Emerson, Honeywell, Yokogawa, GE Vernova, Omron, Mitsubishi Electric

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, but the description adds substantial behavioral context beyond those: hand-verified mapping, ATLAS IDs confirmed against the live matrix, deterministic no-LLM lookup path, $0.20 USDC x402 pricing, and the exact PaymentRequired challenge/retry flow with the signed payload location. These details are necessary for correct invocation and are not covered by the schema or annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and return values, then adds provenance, deterministic behavior, and payment mechanics. Every sentence earns its place: the payment/retry instruction is essential for calling this paid tool, and there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, but the description enumerates the return fields (documented AI/agentic copilot, autonomy level, access, applicable MITRE ATLAS techniques) and explains data provenance and deterministic behavior. Combined with the x402 payment instructions and the readOnly/openWorld annotations, the definition is complete enough for an agent to select, invoke, and interpret the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage and documents the single vendor parameter with concrete OT/ICS examples. The tool description adds no additional parameter semantics such as accepted aliases, case sensitivity, or matching behavior, so the baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb 'lookup' and resource 'AI/agentic copilot exposure', scoped to OT/ICS vendors, and names the returned artifacts (documented copilot, autonomy level, access, MITRE ATLAS techniques). This distinguishes it from generic sibling exposure tools such as getAssetExposure or getVendorRisk.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear use context: it is an AI/agentic copilot exposure lookup specifically for OT/ICS vendors, and it explains the key risk differentiator it returns. It does not explicitly say when not to use it or route the agent to closest alternatives like getAiAttackFeasibility or getAiUplift, so it stops short of full when-to-use guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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