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Intel Threadlinqs MCP

Attack Flow

get_attack_flow
Read-onlyIdempotent

Retrieve the causal MITRE ATT&CK flow for a threat: a DAG of actions, conditions, operators, and assets. Shows what actually caused what, with per-node techniques and tactics.

Instructions

Get the analyst-authored MITRE ATT&CK Flow for a threat: a causal DAG of actions, conditions, operators and assets, with per-node technique ids, tactics and descriptions. This is asserted causality — what actually caused what — not a flat technique list. Check generator: 'harness' is authored, 'derived' is timeline ORDERING and must not be read as causality. Use get_flow_similar_threats to find threats sharing a causal sequence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
viewNo'ir' (default) returns the compact flow IR plus validation findings; 'nodes' returns the denormalized node/edge/asset projection with technique and tactic columns already joined.
threat_idYesThreat ID (e.g. TL-2026-1916)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
flowNo
generatorNo'harness' = analyst-authored causality. 'derived' = timeline ORDERING only — must not be read as causality. 'unknown' = published before provenance was tracked; treat as not authoritative.
threat_idYes
flow_validNo
node_countNo
flow_errorsNo
flow_warningsNo
Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive behavior, so the description adds more useful behavioral context. It explains how to interpret the 'generator' field and asserts that 'derived' ordering must not be read as causality, which is valuable beyond what annotations or schema provide.

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 focused sentences, each carrying necessary information: what the tool returns, an important causal interpretation caveat, and an alternative tool for similar causal sequences. No filler is present, and the most relevant definitions come first.

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 rich annotations, full parameter coverage, an output schema, and a detailed semantics explanation, the description fully equips an agent to understand what the tool returns and how to interpret it. The alternate tool reference adds extra context for when this tool is the wrong choice.

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%, so the parameters and their differences are already well documented. The description does not add much parameter-level detail, but it does clarify the semantic meaning of the returned data. With a high-coverage schema, a baseline of 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?

States a specific verb and resource ('get the analyst-authored MITRE ATT&CK Flow for a threat') and defines the result as a causal DAG of actions, conditions, operators, and assets. It explicitly contrasts itself with a flat technique list, which makes its purpose clear and distinguishes it from sibling tools.

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?

Provides explicit usage guidance by stating the tool returns asserted causality rather than a flat technique list, and warns against misreading 'derived' timelines as causal. It also names get_flow_similar_threats as the alternative for finding threats sharing a causal sequence.

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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