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threadlinqs-cmd

Intel Threadlinqs MCP

Get Actor Profile

get_actor
Read-onlyIdempotent

Retrieve a concise threat-actor profile by name or alias, including metadata, attribution, MITRE techniques, IOC counts, and relationships. Use follow-up tools for full details.

Instructions

Get a lean threat-actor profile by name or alias: actor metadata, attribution counts, attributed-threat summary rows, MITRE tactic rollup + technique ids, IOC category counts (no raw values), CVE/CWE/tool summaries, and relationships. For heavy detail use the follow-up tools: get_threat(id) for a full threat, search_detections / get_detection_detail for detection bodies, search_iocs for IOC values, get_infrastructure_pivots for shared infrastructure.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesActor name or alias (e.g. 'APT29', 'Lazarus Group')

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
cvesNo
actorYes
mitreNo
toolsNo
countsNo
targetsNo
threatsNo
relationshipsNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds meaningful behavioral context: it returns 'IOC category counts (no raw values)', explicitly excluding raw IOCs, and lists summary-level data. This goes beyond the annotations without contradicting them.

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 two sentences: the first states the purpose and contents, the second lists alternatives. Every sentence earns its place, with no redundant filler or unnecessary elaboration.

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?

Given the tool has a rich output schema, the description need not enumerate return values. It covers the 'lean' nature, key data categories, and explicitly directs to follow-up tools for heavy detail. For a single-parameter read-only operation, this is fully sufficient for correct selection and invocation.

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% — the 'name' parameter already includes 'Actor name or alias (e.g. 'APT29', 'Lazarus Group')'. The description's phrase 'by name or alias' merely reinforces the schema, adding no extra semantic detail beyond what is already structured.

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?

The description uses a specific verb and resource: 'Get a lean threat-actor profile by name or alias' and enumerates the exact contents (actor metadata, attribution counts, MITRE rollup, etc.). It clearly distinguishes itself from follow-up tools like get_threat and search_detections by positioning itself as the 'lean' entry point.

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?

It explicitly provides when-to-use and alternatives: 'For heavy detail use the follow-up tools: get_threat(id) for a full threat, search_detections / get_detection_detail for detection bodies, search_iocs for IOC values, get_infrastructure_pivots for shared infrastructure.' This directly addresses usage trade-offs.

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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