suggest_dining

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint. The description adds that it operates on partial keywords and covers multiple entity types, which is useful context beyond the annotations but does not contradict them. No side effects are implied, consistent with read-only behavior.

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?

A single, concise sentence with no filler. The key purpose and scope are front-loaded. All necessary information fits efficiently within one line.

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?

The tool is simple and has an output schema, so return values are defined. However, the description does not mention when to prefer this tool over suggest_locations or suggest_tabelog, especially in a rich sibling ecosystem. The openWorldHint annotation suggests possible unknown behaviors, but the description doesn't address them.

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 all three parameters (query, limit, provider) are already documented. The description adds little beyond restating the entity types covered by query, which is already in the schema examples. It meets the baseline without adding extra nuance.

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 the verb 'autocomplete' and the resource 'search query', and lists specific entity types (restaurants, cafes, stations, areas, food genres). It is distinct from generic search, but does not explicitly differentiate from sibling suggest_tabelog or suggest_locations, which are also suggestion tools.

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 the tool is for autocomplete/search-as-you-type scenarios, but provides no explicit when-to-use or when-not-to-use guidance versus the many sibling search and suggestion tools. The broad entity list hints at coverage but lacks clear exclusions or alternatives.

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