suggest_areas

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

With no annotations provided, the description must carry the behavioral burden. It states the core behavior ('Returns matching area suggestions') but does not disclose details such as result limits, ordering, case sensitivity, or output format beyond what the parameter schema covers. While adequate for a simple autocomplete, it lacks depth on any potential side effects or limitations.

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 a single, efficient sentence that front-loads the primary action and resource. It contains zero waste and every word adds value, making it easy for an agent to parse quickly.

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?

Given the low complexity (2 params, no output schema), the description is largely complete for an autocomplete tool. It states the purpose and the return behavior. However, it could be more complete by mentioning how this differs from get_areas or suggest_positions, and by clarifying that the 'raw' parameter controls output format (though that is in the schema). Overall, it is close to sufficient but not fully explicit.

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?

Schema description coverage is 100%, so both parameters ('text' and 'raw') are already fully described in the input schema. The description adds no additional parameter semantics—it only mentions 'partial input' which corresponds to the 'text' parameter but does not elaborate on the 'raw' parameter or how the two interact. Baseline score of 3 is appropriate.

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?

The description clearly states a specific verb ('Autocomplete') and resource ('region/city names'), and additionally says it 'Returns matching area suggestions for partial input.' This makes the tool's function unambiguous and distinguishes it from siblings like get_areas (which likely lists full areas) and get_areas_subtree (which likely returns hierarchical subtrees).

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 implies usage for partial input ('for partial input') but does not explicitly contrast this tool with alternatives like get_areas or suggest_positions. It lacks 'when not to use' guidance or mention of sibling tools, leaving the agent to infer appropriate usage from context alone.

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