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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, covering attribution counts, MITRE tactic and technique rollups, IOC category summaries, and relationship insights.

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. Tactic keys are canonicalised (the corpus writes both "Credential Access" and "credential-access") and the rollup counts DISTINCT TECHNIQUES per tactic; mitre.technique_ids is capped at 60 against mitre.techniques_total. relationships splits into shared_infra / shared_techniques / shared_tooling with the type re-derived from the value, because corr_attribution types tool names as hashes. An empty actor_relationships means UNRECORDED, not unrelated — see actor_relationships_coverage. 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
actor_relationshipsNo
actor_relationships_coverageNoPresent only when actor_relationships is empty: says the baseline has no row, not that the actor is unrelated.
Behavior5/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description goes well beyond that by disclosing canonicalisation of tactic keys, DISTINCT technique counting, the 60-cap on mitre.technique_ids, relationship re-derivation, and the meaning of empty relationship lists. These are non-obvious behaviors an agent needs to understand the output.

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?

Though long, every clause carries semantic weight: the output inventory is compact, edge-case behavior is stated directly, and follow-up routing is front-loaded. The long sentence is dense but not bloated, and important caveats are placed ahead of alternatives.

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 output schema exists, the description need not re-specify return shapes. It covers the response's semantics, known data-quality quirks, the coverage caveat for relationships, and alternative tools for heavier detail. Nothing needed to invoke or interpret this tool correctly is missing.

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 schema already documents name as 'Actor name or alias (e.g. 'APT29', 'Lazarus Group')'. The description's 'by name or alias' repeats rather than extends this. No additional parameter-level semantics are contributed.

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 states a specific verb and resource: 'Get a lean threat-actor profile by name or alias.' It enumerates the exact contents (metadata, attribution counts, MITRE rollups, IOC category counts, summaries, relationships), which clearly distinguishes it from siblings like get_actor_intelligence and get_threat.

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?

The description explicitly says 'For heavy detail use the follow-up tools' and names get_threat, search_detections, get_detection_detail, search_iocs, and get_infrastructure_pivots. It also warns that an empty actor_relationships means 'UNRECORDED' rather than 'unrelated,' giving the agent interpretative 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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