get_entities_by_area

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

With no annotations provided, the description carries the full disclosure burden and largely succeeds: it reveals the non-obvious parent-device inheritance behavior, case-insensitive matching, and the meaning of the lean parameter's token efficiency. It clearly describes the return structure. Only minor gaps remain (e.g., behavior for nonexistent areas, pagination), keeping it just short of a 5.

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

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

The description is well-organized with a one-line summary followed by standard docstring sections (Args, Returns, Examples) that are easily scannable. It is slightly verbose for a tool description, but every section earns its place, and the examples are instructive without being padded.

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

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

For a 3-parameter query tool, the description is thorough: all parameters are documented with extra semantics, the return structure is specified, behavioral edge cases (inheritance, case folding) are covered, and actionable examples are provided. With an output schema available, nothing material is left unaddressed.

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

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

With 0% schema coverage, the description must compensate — and it does thoroughly. It adds case-insensitivity semantics to 'area', clarifies 'domain' as a secondary filter with an example, and explains 'lean' as producing 'token-efficient entity records.' The examples further demonstrate parameter composition, adding meaning well beyond the bare boolean/string types in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

"Get all entities assigned to a specific Home Assistant area (room)" uses a specific verb+resource and clearly scopes the operation to area-based lookups, distinguishing it from siblings like get_entity (single entity), search_entities_tool, and domain_summary_tool. The opening line is immediately identifiable in purpose with no ambiguity.

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

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

The description provides solid functional context (case-insensitive matching, parent-device inheritance) but never explicitly guides tool selection versus overlapping siblings like search_entities_tool, list_entities, or domain_summary_tool. Usage is implied through the detailed behavior rather than stated — no when-to-use or when-not-to-use guidance or named alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.