ikea_suggest

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

With no annotations provided, the description carries the full behavioral disclosure burden. It discloses that results include suggested query completions with match counts and a small number of top matching products, and explicitly states the clean empty response for no-match queries. It does not describe ranking or formatting details, but for a suggestion endpoint this is solid transparency.

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 sentences with no waste. The first sentence states the core purpose, the second details the response composition, and the third covers the edge case of no matches. Every sentence earns its place and the description is front-loaded with the primary intent.

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 simple suggestion tool with one required parameter, no output schema, and no nested objects, the description provides a complete mental model: what it returns, its scope, and the no-match behavior. It could slightly enhance completeness by noting how the optional country/language parameters affect results (e.g., localization, availability), but that is a minor gap at this complexity level.

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 the schema already documents all four parameters. The description adds useful semantic context by clarifying that 'q' accepts partial or full search terms (directly relevant to typeahead usage) and that 'size' controls the top-product count. This adds value beyond the raw schema while remaining concise.

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 and resource: 'Get IKEA search-box typeahead suggestions.' It explains exactly what the tool returns—query completions with match counts plus a small number of top matching products—and distinguishes it from full-search siblings like ikea_search by focusing on autocomplete/typeahead behavior. This is specific, unambiguous, and easy for an agent to act on.

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 conveys this is the right tool for typeahead/autocomplete-style lookups where the query is partial or full, and it implies lightweight suggestions rather than full search results. It does not explicitly name ikea_search or other alternatives or state when not to use it, but the use case is clear enough that an agent can infer appropriate invocation.

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