Get Mercari search suggestions for a partial keyword in Mercari's own relevance order. Returns an empty list for obscure or gibberish input, a normal result.
Mercari search autocomplete. Returns Mercari's own search-suggestion list for a partial keyword, in its own relevance order. An empty suggestion list is a normal outcome for obscure or gibberish input.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Partial keyword to get suggestions for |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and does add real value: it discloses that results come 'in its own relevance order' and, importantly, that 'an empty suggestion list is a normal outcome for obscure or gibberish input' — this preempts an agent misreading an empty result as failure. It omits rate limits or whether input is normalized, so it is not exhaustive.
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?
Three short sentences, front-loaded with the purpose, followed by ordering and the empty-result caveat. No padding; each sentence carries distinct information.
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 single-parameter autocomplete tool with no output schema, the description covers what is returned, the ordering, and the normal-empty-result case — enough for an agent to call it and interpret the response. It stops short of distinguishing the suggestion list from mercari_search results, which would make it fully complete.
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 coverage is 100% for the single 'query' parameter, so the schema already documents the input. The description's 'partial keyword' wording confirms the expected input style but adds no format, length, or normalization details beyond what the schema states. Baseline 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 states a specific verb and resource: 'Returns Mercari's own search-suggestion list for a partial keyword.' An agent immediately knows this is the autocomplete/suggestion endpoint, and the name reinforces it. It does not explicitly differentiate from siblings like mercari_search, but the purpose itself is unambiguous.
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 phrase 'for a partial keyword' implies the appropriate use case, but the description never says when to reach for this over mercari_search or why the suggestion list is useful (e.g., keyword discovery). Usage is implied rather than stated, with no alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.