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Mipiti
by Mipiti

list_effective_entities

Retrieve the effective set of entities for a threat model, including trust boundaries, components, assets, and attackers, each tagged with its provenance (own or inherited) and fully-qualified ID for unambiguous cross-model references.

Instructions

Effective entity set (own ⊕ inherited) keyed by kind.

Returns the entity set this model sees after composition with ancestors: trust boundaries, components, assets, attackers, and (when applicable) attack paths. Each entry carries its provenance — whether it originates on this model or is inherited from an ancestor — plus a fully-qualified id so cross-model references are unambiguous.

Pair with list_effective_control_objectives and get_effective_coverage to see how inherited topology contributes to coverage credit.

Return shape::

{
  model_id, flag_enabled,
  kinds: {
    trust_boundaries: [{kind, qualified_id, owner_model_id,
      owner_title, origin, entity}, ...],
    components: [...], assets: [...], attackers: [...], ...
  },
  total, page, page_size,
}

When composition is disabled on the backend, kinds is returned with every kind mapped to an empty list and flag_enabled: false.

Omitting page / page_size defaults to page=1, page_size=100 — the response is paginated and no longer returns every entity in a single call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNooptional single entity kind to restrict the response to (e.g. ``"attackers"``, ``"assets"``, ``"components"``, ``"trust_boundaries"``). When omitted, all kinds are returned.
pageNo1-indexed page number (default ``1``).
model_idYesID of the threat model.
page_sizeNoentries per page (default ``100``).
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations provided, the description fully carries the burden. It discloses composition behavior, provenance tracking, return shape, pagination defaults, and the fallback when composition is disabled (empty kinds with flag_enabled: false). No contradictions.

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?

The description is well-structured with paragraphs, a bullet list, and a code block for the return shape. It is front-loaded with the main purpose and every sentence adds value, avoiding redundancy.

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 output schema is included in the description, behavioral details are thorough, and parameter semantics are mostly covered, the description is complete. It covers pagination, composition disabled edge case, and return structure. Error conditions are not mentioned but are typically implied.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 80% (4 of 5 parameters have descriptions). The description adds value by explaining pagination defaults and the effect of omitting the kind parameter, but does not address the undocumented server_version parameter. Overall, it provides useful context beyond the schema.

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 states the tool returns the effective entity set after composition with ancestors, specifying the kinds included (trust boundaries, components, etc.) and provenance. It distinguishes from siblings like list_effective_control_objectives by pairing them as complementary 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?

The description provides clear context on when to use this tool (to get inherited topology) and explicitly pairs it with related tools for coverage credit. However, it does not explicitly state when not to use it or provide direct alternatives among siblings.

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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