Skip to main content
Glama
Mipiti
by Mipiti

Get Threat Model

get_threat_model

Retrieve a complete threat model by its ID, including trust boundaries, assets, attackers, control objectives, and assumptions.

Instructions

Get a specific threat model by ID.

Returns the full threat model including trust boundaries, assets, attackers, control objectives, and assumptions.

Important for agents reading model state:

  • Assets and attackers may carry deleted: true (soft-deleted). Exclude these when showing "what's in the model now"; include them only when discussing history or offering restore. Restore an entity via restore_entity (entity_type="asset") / restore_entity (entity_type="attacker").

  • Control objectives may carry removed: true (tombstone — the (asset, attacker) pair was removed in a later version). Exclude these from coverage math and LLM prompts; they exist to keep CO IDs stable so controls referencing them can be detected as "orphaned" rather than silently rebinding.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
versionNoOptional specific version number. Defaults to latest.
model_idYesID of the threat model.
include_cosNoInclude control objectives inline.
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.57.0

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations, the description carries the full disclosure burden and does so well. It reveals soft-deleted assets/attackers, tombstoned control objectives, how to treat them in prompts and coverage math, and which restore_entity calls to use. This is decision-critical behavioral context beyond the schema.

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?

A one-sentence summary is followed by two tightly scoped bullets, and every sentence adds agent-relevant detail. The formatting is front-loaded and scannable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description thoroughly covers return semantics and hidden model-state behavior, and an output schema is present to document the return shape. The main gap is server_version, a required parameter with no schema or description explanation, which prevents full self-sufficiency.

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?

The schema already documents three of the four parameters, so the description does not need to repeat them. However, it does not clarify the required server_version parameter or explicitly reconcile its claim that control objectives are included with the include_cos default of false.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a concrete verb ('Get'), a specific resource ('threat model'), and a selection mechanism ('by ID'), and it enumerates the contents of the returned full threat model. This differentiates it from lineage tools like list_threat_models, though it does not explicitly name alternative tools.

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 clearly frames this as the endpoint for agents that need the full model state and gives operational context for interpreting that state. It does not explicitly say when to prefer query_threat_model or list_threat_models, so exclusion guidance is missing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools