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get_entity

Retrieve a single O3DE entity's name, transform, parent, and components as JSON to inspect or debug entity data in the editor.

Instructions

Return one entity's name, transform, parent and component list as JSON.

Served natively by the AiCompanion gem's C++ (get_entity request type, gem 0.4.0 or later) with no editor Python, so it is the cheapest way to look at a single entity and works in the gem's secure mode. On gem 0.6.0 the reply also carries non_uniform_scale and effective_scale, and ids are decimal strings. An unknown id is the error not_found (gem 0.5.0 and earlier answered with the gem's own {"entity_id": ..., "error": ...} object instead).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations the description carries the full burden, and it does so well: native C++ execution with no editor Python, secure-mode compatibility, version-gated response fields, decimal-string ids on 0.6.0, and explicit error behavior for an unknown id ('not_found'). The only gaps are permissions/auth requirements and any rate or size limits.

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

Conciseness3/5

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

The first sentence is an excellent front-loaded summary. The remainder is dense with gem-version history (0.4.0/0.5.0/0.6.0) and legacy error-shape detail, some of which is useful but much of which is marginal for an agent selecting the tool.

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?

An output schema exists, so return values need not be spelled out, yet the description still characterizes them and adds error and version behavior. For a simple one-parameter read tool, the definition is largely complete; only the entity_id format/derivation is left unaddressed.

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 0% for the single required 'entity_id' parameter, so the description must compensate. It only indirectly adds meaning by noting that ids are decimal strings on gem 0.6.0; it never states what an entity_id is or how to obtain one, leaving a real gap.

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 first sentence names a specific verb and resource and enumerates exactly what is returned (name, transform, parent, component list) as JSON. It also calls itself 'the cheapest way to look at a single entity,' which implicitly contrasts with heavier siblings like get_entity_tree, but it never names those alternatives explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'The cheapest way to look at a single entity' implies a use case, and 'works in the gem's secure mode' hints at context, but there is no explicit when-to-use vs when-not, and no sibling (get_entity_tree, get_entity_components, get_transform, list_entities) is named as the alternative. Guidance is present but left to inference.

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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