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threadlinqs-cmd

Intel Threadlinqs MCP

Malware Intelligence

get_malware_intelligence
Read-onlyIdempotent

Look up a malware family by name to get its type, prevalence, deploying threats, associated actors, and common ATT&CK techniques for faster threat analysis and response.

Instructions

Pivot on a malware FAMILY by name (e.g. "LockBit", "Vidar", "Emotet"). Returns the canonical family + type, prevalence (threat/actor counts, first/last seen), the threats deploying it, the actors using it, and its most-common ATT&CK techniques. For an offensive TOOL (Cobalt Strike, Mimikatz) use get_tool_intelligence instead. Call resolve_entity first if unsure of the canonical name.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesMalware family name (e.g. "LockBit", "Vidar")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
actorsNo
matchedYes
threatsNo
canonicalNo
prevalenceNo
entity_typeNo
top_techniquesNo
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, covering the safety profile. The description adds value by disclosing the returned data structure and the pivot-by-family semantic (returns collective family data rather than a single entity). No contradiction. Minor gap: doesn't mention output shape/limit behavior, but output schema exists to cover that.

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?

Three sentences, all dense with actionable info: pivot target, return fields, alternative tool, and a preceding step (resolve_entity). Zero filler. Front-loaded with the core verb+resource.

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

Completeness4/5

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

For a read-only lookup with 1 param, 100% schema coverage, and an output schema present, the description covers purpose, return contents, alternatives, and preprocessing. The output schema handles return-format detail. Only slight gap is not listing the specific output schema fields explicitly, but that is redundant given the output schema exists.

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

Parameters4/5

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

Schema coverage is 100% and the single 'name' param is documented in the schema. The description adds semantic value by explaining the param expects a canonical family name (not arbitrary string) and instructs resolve_entity to canonicalize if unsure. Baseline 3 plus meaningful context about canonical-name requirement.

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?

Description states a specific verb+resource: 'Pivot on a malware FAMILY by name' and enumerates exact return fields (canonical family+type, prevalence, threats, actors, ATT&CK techniques). It clearly distinguishes from sibling get_tool_intelligence by contrasting malware family vs offensive tool.

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

Usage Guidelines5/5

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

Explicitly names an alternative tool (get_tool_intelligence) and states when NOT to use this one ('For an offensive TOOL... use get_tool_intelligence instead'). Also instructs calling resolve_entity first if the canonical name is uncertain, and provides concrete examples (LockBit, Vidar, Emotet).

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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