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Glama

List entities exposed to an assistant

entities_list_exposed_entities
Read-onlyIdempotent

List all entities exposed to a given voice assistant by filtering Home Assistant's full exposure map client-side for conversation, Alexa, or Google Assistant.

Instructions

List every entity currently exposed to one voice assistant.

Home Assistant has no per-assistant exposure query, so this fetches the full exposure map via WS homeassistant/expose_entity/list and filters it client-side for the given assistant.

Use when: auditing what one assistant can currently see. Not for: exposure of one specific entity — use entities_get_entity_exposure. Returns: dict with assistant and exposed (list of entity IDs). Errors: raises ValueError when assistant is not one of conversation, cloud.alexa, cloud.google_assistant.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assistantYesVoice assistant identifier: 'conversation', 'cloud.alexa' or 'cloud.google_assistant'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.25.1
    • addedInput schema / properties / assistant / description
      Added value: +"Voice assistant identifier: 'conversation', 'cloud.alexa' or 'cloud.google_assistant'."
  2. First observedv0.3.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already establish the safe read-only, idempotent, non-destructive profile, and the description adds substantial context beyond them: it explains the internal WebSocket call and client-side filtering, documents the return shape, and states the exact ValueError condition and valid assistant identifiers. This is rich operational disclosure that goes well past what annotations provide.

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 front-loaded with purpose, then mechanism, usage guidance, return shape, and error behavior. Every sentence carries distinct information, and the Use/Not for/Returns/Errors structure makes it easy to scan.

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?

For a one-parameter read tool with rich annotations and an output schema, the description is complete: it covers purpose, alternatives, implementation caveats, return shape, and error cases. Nothing an agent needs to invoke or interpret this tool 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 the single `assistant` parameter is already fully documented in the schema with the same valid values. The description restates those values but adds no new syntax, format, or edge-case meaning beyond the schema, so the baseline 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?

The description states a specific verb and resource: list every entity exposed to one voice assistant. It explicitly distinguishes itself from the sibling `entities_get_entity_exposure`, which handles a single entity's exposure, so an agent can select between them without opening either schema.

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?

It gives explicit use conditions ('Use when: auditing what one assistant can currently see') and an explicit exclusion ('Not for: exposure of one specific entity — use `entities_get_entity_exposure`'). The alternative tool is named directly, leaving no inference required.

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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