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by io.github.mitigant
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get_attacks_by_threat_actor

Read-only

Find the managed attacks that demonstrate a named threat actor's real techniques, for one cloud service -- e.g. 'which Azure attacks demonstrate Scattered Spider', or to plan a red team exercise around one actor's known behavior. Get the actor's exact name from list_threat_actors first. Each result includes the same fields as list_attacks, plus matchedThreatActorTechniques: exactly which of that attack's own technique id(s) this actor is cited for (never that attack's full technique list, since one attack can implement several techniques and only some may belong to this actor). An actor with no mapped technique yet returns an empty list, not an error.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "cloud_service": "<cloud_service>",
      "threat_actor_name": "<threat_actor_name>"
    },
    "name": "get_attacks_by_threat_actor"
  }
}

Input Schema

NameRequiredDescriptionDefault
cloud_serviceYesWhich cloud provider's catalog to search
threat_actor_nameYesThe actor's exact name from list_threat_actors (e.g. 'Storm-0940', 'Scattered Spider'). An unknown or misspelled name returns an empty list, not an error -- call list_threat_actors first if unsure of the exact spelling.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true and destructiveHint=false; the description goes well beyond that by disclosing the result shape ('same fields as list_attacks, plus matchedThreatActorTechniques') and clarifying that the matched-technique field is a subset, not the attack's full technique list. It also documents the empty-list-not-error edge case, which an agent would otherwise misread as a failure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core action and use cases, then the prerequisite, then result semantics. The parenthetical explaining matchedThreatActorTechniques is long but earns its place by preventing a common misreading; overall it is slightly verbose but not padded.

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 no output schema, the description carries the burden of explaining return values and does so: it names the extra field, explains its meaning, and states the empty-list behavior. For a two-parameter read tool with annotations covering safety, nothing an agent needs to call it 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 coverage is 100%, and both parameters are already documented in the schema, including the exact-name requirement and enum values for cloud_service. The description reinforces the exact-name rule but adds no syntax or format detail beyond what the schema provides, so the baseline 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?

States a specific verb and resource ('Find the managed attacks that demonstrate a named threat actor's real techniques, for one cloud service') and grounds it with two concrete example queries. It is clearly distinguishable from list_attacks and list_threat_actors, which it references by name.

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?

Gives explicit use cases (threat-actor research, red-team planning) and an explicit prerequisite: get the actor's exact name from list_threat_actors first. It also routes the agent away from a wrong path by warning that a misspelled name yields an empty list rather than an error.

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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