Autocomplete restaurant, area, and genre suggestions from a keyword to help AI assistants build accurate Japanese restaurant searches before querying Tabelog.
Autocomplete restaurants, areas and genres for a keyword.
| Name | Required | Description | Default |
|---|---|---|---|
| keyword | Yes | ||
| current_latitude | No | ||
| current_longitude | No |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not state that this is a read-only, side-effect-free lookup, nor does it describe return shape, result limits, or what happens when a keyword yields no matches. 'Autocomplete' hints at lightweight suggestions but no behavioral specifics are given.
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 well-formed sentence with no filler and the purpose front-loaded. It is efficient, though its terseness borders on under-specification rather than being optimally informative.
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 tool with no annotations and no output schema, the description should explain the geo parameters and the nature of returned suggestions. It omits the lat/long semantics entirely and gives no sense of result shape, leaving the agent under-equipped to call it correctly in context.
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 0%, so the description is responsible for documenting three parameters. It mentions only 'keyword' implicitly and says nothing about current_latitude/current_longitude, which control proximity-based suggestions — a significant unexplained gap.
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 verb 'Autocomplete' with resources 'restaurants, areas and genres' is specific and distinguishes it in spirit from search_restaurants (completions vs full search). However, the description does not explicitly differentiate itself from its sibling search_restaurants or explain what an 'autocomplete' result is, leaving the distinction to inference.
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?
Usage is only implied by the word 'Autocomplete' — the agent can infer it is for typeahead-style suggestions, but there is no explicit when/when-not guidance and no reference to the obvious alternative search_restaurants for full search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.