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Intel Threadlinqs MCP

Technique Co-occurrence Rules

get_technique_rules
Read-onlyIdempotent

Discover MITRE ATT&CK techniques that co-occur in threats, backed by lift with support and confidence. Reveals which techniques appear together to uncover attack correlation patterns.

Instructions

MITRE ATT&CK technique PAIRS mined from the corpus with support, confidence and lift — which techniques travel together far above chance. Each rule carries both technique ids AND their ATT&CK names (technique_a_name / technique_b_name), so a rule is readable without a follow-up lookup. Complements predict_mitre_transitions exactly: that answers sequence (what follows what), this answers co-occurrence (what appears alongside what). Rules come back lift-descending; summary.total_rules reports how many exist in total, so has_more tells you whether the tail was cut. Note minSupport 0.02 — a pair must appear in ~2% of threats to be mined at all, so rare-technique pairs are structurally absent rather than uncorrelated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoDefault 50, max 100.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rulesYes
summaryNo
Behavior5/5

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description additionally reveals the minSupport cutoff of 0.02, the lift-descending sort order, the presence of summary.total_rules and has_more for pagination, and that names are included to reduce follow-up lookups. This goes well beyond the annotations with material behavioral detail.

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 carries distinct and necessary information: core output, adjacent distinction, ordering/pagination, and interpretation caveat. It is front-loaded with the main purpose and remains compact without redundant wording.

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?

The tool has one optional parameter, no destructive behavior, rich annotations, and an output schema. The description still adds crucial output semantics around total rules, has_more, sorting, and the minSupport miners, so an agent can select it and interpret its result without uncovered surprises.

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?

There is only one parameter, limit, and the schema already covers it with default and max values at 100% coverage. The description does not need to add parameter semantics, so the baseline score of 3 applies.

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?

Describes exactly what the tool provides: MITRE ATT&CK technique pairs mined from the corpus with support, confidence, and lift. It clearly describes the co-occurrence focus and explicitly distinguishes it from the sequence-focused predict_mitre_transitions tool, making the resource and intent unmistakable.

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 the only sensible sibling alternative, predict_mitre_transitions, and explains the selection criterion: sequence versus co-occurrence. It also warns about the minSupport threshold, so an agent knows rare-pair results will be absent by design rather than anomalous.

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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