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threadlinqs-cmd

Intel Threadlinqs MCP

Flow-Similar Threats

get_flow_similar_threats
Read-onlyIdempotent

Find threats that share a causal sequence of ATT&CK techniques by scoring ordered-bigram cosine over Flow transitions, returning shared chains like T1003>T1021.

Instructions

Find threats that share a causal SEQUENCE of techniques with this one, scored by ordered-bigram cosine over ATT&CK Flow transitions. This sees what no other channel can: every existing similarity signal compares flat sets, so two threats can share an identical attack ORDER while sharing no indicator, CVE or actor. Returns the shared transitions (e.g. 'T1003>T1021') so the claim is inspectable. Scored independently and NOT folded into get_similar_threats' blended score.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax neighbours (default 20, max 100)
min_scoreNoDrop neighbours below this sim_flow (0-1)
threat_idYesThreat ID (e.g. TL-2026-1916)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
countNo
reasonNoPresent only when data is empty; distinguishes "no flow published" from "flow published, no neighbours".
threat_idYes
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral detail beyond annotations: the scoring algorithm, the ATT&CK Flow transition concept, and the expectation that it returns inspectable shared transitions like 'T1003>T1021'. No contradiction with 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?

Every sentence earns its place: the core operation, the uniqueness explanation, the return contract, and the independence from get_similar_threats. It is front-loaded with the primary verb and resource, and there is no padding.

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?

With the output schema present, parameter meanings fully documented, and annotations covering side effects, the description is complete enough for an agent to successfully call this tool. The remaining constraints like min_score and limit are already captured in the schema.

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%, with meaningful definitions already provided for threat_id, limit, and min_score. The description does not need to restate parameter details, and it does not meaningfully expand beyond what the schema says. Baseline 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?

The description clearly identifies the specific action: finding threats that share a causal SEQUENCE of techniques, using ordered-bigram cosine over ATT&CK Flow transitions. It also distinguishes this tool from the sibling similarity tool by explicitly stating its score is NOT folded into get_similar_threats' blended score.

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?

It gives clear context on when this tool is valuable: when attack ORDER matters and flat-set similarity signals are insufficient. It names get_similar_threats as the alternative and contrasts its blended scoring, but it stops short of explicitly listing when-not-to-use conditions.

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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