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Search entities, devices and areas

search_deep_search
Read-onlyIdempotent

Fuzzy-search entities, devices, and areas together in one ranked list. Use when you don't know whether the target is an entity, device, or area.

Instructions

Fuzzy-search entities, devices and areas together in one ranked list.

Scores states (tagging automation.* entities as kind 'automation', others as 'entity'), devices and areas against query the same way as the single-kind search tools, merges all matches, and returns the top limit sorted descending.

Use when: you don't know whether what you're looking for is an entity, device or area. Not for: results scoped to one kind — use search_search_entities, search_search_devices or search_search_areas. Returns: list of dicts tagged with kind ('entity'/'automation'/ 'device'/'area'), each with kind-specific fields plus score, up to limit entries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of ranked results to return; defaults to 20.
queryYesSearch text to fuzzy-match across entities, devices and areas.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.25.1
    • addedInput schema / properties / limit / description
      Added value: +"Maximum number of ranked results to return; defaults to 20."
    • addedInput schema / properties / query / description
      Added value: +"Search text to fuzzy-match across entities, devices and areas."
  2. First observedv0.3.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so safety is covered. The description adds real behavioral detail beyond them: it explains the scoring/merging algorithm, the 'automation' vs 'entity' kind classification, and the descending sort — useful context an agent couldn't derive from the annotations.

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?

Front-loaded with the one-line purpose, then algorithm, then Use/Not-for routing, then return shape. Every sentence earns its place with no filler.

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 2-param search tool with annotations and an output schema, this is complete: selection guidance, algorithmic behavior, kind tagging and return shape are all present, so an agent can call it correctly without opening the schema.

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 100% so the baseline is 3, but the description adds meaning: `query` is fuzzy-matched across all three resource kinds, and `limit` caps the ranked list after merge/sort rather than per-kind. That is more than the schema states.

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?

States a specific verb (fuzzy-search) plus the exact resources (entities, devices, areas) and the distinguishing behavior (single ranked merged list). This clearly separates it from the single-kind search siblings.

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?

Explicit 'Use when' clause gives the selecting condition (unknown whether the target is an entity, device or area), and 'Not for' names the three alternatives (search_search_entities/devices/areas) for the single-kind case. Nothing is 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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