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OT Intel API

ICS Detection Artifact Retrieval

getDetectionArtifacts
Read-only

Returns YARA/Sigma detection rules for an ICS malware family or threat actor. Rules sourced from public corpus (Florian Roth signature-base, CISA advisories) are marked validated:true and safe for staging. DeepSeek-synthesised rules carry validated:false and require lab testing. Designed for automated threat hunting pipelines that commit rules to SIEMs and EDRs. Price: $0.05 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
formatNoRule format filter (default: all)all
targetYesMalware or actor name e.g. PIPEDREAM, INDUSTROYER2, TRITON, SANDWORM, CHERNOVITE

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 only cover readOnlyHint and openWorldHint, yet the description adds substantial operational detail: the validated:true vs validated:false provenance distinction (public corpus vs DeepSeek synthesis), the requirement to lab-test unvalidated rules, and the full x402 payment flow including the unpaid-call challenge and the _meta["x402/payment"] retry mechanism. This is exactly the kind of auth/payment/trust context annotations cannot express.

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?

Five sentences, zero filler, and correctly front-loaded: what the tool returns, then rule provenance/trust, then intended consumer, then the payment mechanics needed to invoke it successfully. Every sentence earns its place.

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, so the description carries the return-value burden and does so by explaining what the rules are and how the validated flag should be interpreted. Combined with the payment/retry instructions, an agent has everything needed to call this correctly on the first attempt.

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?

Schema description coverage is 100% and the format enum is self-documenting, so the baseline of 3 applies. The description says rules are returned for a named 'ICS malware family or threat actor', reinforcing the target parameter's meaning, but adds no new syntax or constraint beyond what the schema already provides.

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 concrete verb+resource ('Returns YARA/Sigma detection rules for an ICS malware family or threat actor') and names the domain explicitly (ICS malware/actors), which is enough to distinguish it from siblings like getMalwareProfile or getIocEnrichment without opening a schema.

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?

Gives clear context of use: 'Designed for automated threat hunting pipelines that commit rules to SIEMs and EDRs.' That framing tells an agent when the tool fits, but it never names an alternative sibling or an explicit when-not-to-use condition.

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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