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HiTechLabTN

hass-mcp

by HiTechLabTN

entity_action

Control any Home Assistant device by turning it on, off, or toggling it. Specify the entity ID and action, with optional parameters like brightness or temperature for tailored automation.

Instructions

Perform an action on a Home Assistant entity (on, off, toggle)

Args: entity_id: The entity ID to control (e.g. 'light.living_room') action: The action to perform ('on', 'off', 'toggle') params: Optional dictionary of additional parameters for the service call

Returns: The response from Home Assistant

Examples: entity_id="light.living_room", action="on", params={"brightness": 255} entity_id="switch.garden_lights", action="off" entity_id="climate.living_room", action="on", params={"temperature": 22.5}

Domain-Specific Parameters: - Lights: brightness (0-255), color_temp, rgb_color, transition, effect - Covers: position (0-100), tilt_position - Climate: temperature, target_temp_high, target_temp_low, hvac_mode - Media players: source, volume_level (0-1)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYes
paramsNo
entity_idYes
Behavior2/5

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

With no annotations provided, the description is the sole source of behavioral disclosure. It mentions the action and return value but does not disclose side effects, required permissions, error behavior for invalid actions or missing entities, or whether the operation is reversible. For a mutation tool, this is a safety-relevant gap.

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?

The description is well-organized with a one-line summary, argument breakdown, return statement, examples, and domain-specific details. It remains scannable, though the domain-specific section slightly duplicates what the examples already show (e.g., brightness appears in both). No unnecessary filler.

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

Completeness3/5

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

For a tool with no annotations and no output schema, the description thoroughly covers parameter semantics but leaves important gaps: the return value is vaguely 'The response from Home Assistant', error and edge-case behavior is absent, and it does not clarify when to use this versus call_service_tool. It is adequate but not fully complete.

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

Parameters5/5

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

Schema description coverage is 0%, so the description is the only source of parameter meaning. It explains each argument, provides concrete entity_id examples, enumerates valid action values, defines params as an optional dictionary, and gives domain-specific parameter details (brightness, temperature, position, etc.) — far exceeding the bare 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 opening sentence clearly states the tool's function: 'Perform an action on a Home Assistant entity (on, off, toggle)'. The examples with entity_id and action values make the scope unmistakable, and the domain-specific parameters distinguish it from read tools like get_entity and the broader call_service_tool.

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 examples and domain-specific parameter list imply usage contexts (lights, covers, climate, media players), but the description never explicitly compares this tool to sibling call_service_tool or states when to prefer one over the other. The usage guidance is mostly inferred rather than explicit.

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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