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HiTechLabTN

hass-mcp

by HiTechLabTN

search_entities_tool

Find Home Assistant entities by searching IDs, names, and attributes. Retrieve matching results with domain counts, and set a limit to narrow down the output.

Instructions

Search for entities matching a query string

Args: query: The search query to match against entity IDs, names, and attributes. (Note: Does not support wildcards. To get all entities, leave this blank or use list_entities tool) limit: Maximum number of results to return (default: 20)

Returns: A dictionary containing search results and metadata: - count: Total number of matching entities found - results: List of matching entities with essential information - domains: Map of domains with counts (e.g. {"light": 3, "sensor": 2})

Examples: query="temperature" - find temperature entities query="living room", limit=10 - find living room entities query="", limit=500 - list all entity types

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the burden of explaining behavior. It discloses the return structure, the lack of wildcard support, and the effect of leaving query blank, but does not explicitly state read-only nature, though it is implied.

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 sections for args, returns, and examples. It is somewhat detailed but each part adds value, making it appropriately concise without being overly verbose.

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 tool's complexity and the lack of annotations, the description is remarkably complete. It covers functionality, parameters, return format, limitations, and alternatives, leaving little ambiguity for the agent.

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?

The description adds significant meaning to both parameters: query is explained as matching against IDs, names, and attributes, and limit is defined as a maximum result count with a default. It also clarifies edge cases like blank query.

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's function: searching for entities by a query string. It also differentiates from sibling tools like list_entities by explicitly noting the alternative for retrieving all entities.

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?

The description provides explicit guidance on when to use the tool, including a note about wildcard limitations and a clear alternative (list_entities) for fetching all entities. Examples illustrate typical usage.

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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