instacart_search

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly explains the tool's behavior: returns term-level suggestions with a representative thumbnail, mirrors the site's search box dropdown, is scoped to one store, and uses public data. This provides rich context beyond the bare function.

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 three sentences, front-loaded with the core purpose. Each sentence adds distinct value: the scope ('at a store'), the output type ('autosuggestions... dropdown'), and the nature of the data ('term-level', 'not a product list', 'public data'). No fluff or redundancy.

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 relatively simple, and the description covers the essential behavior, scope, and data source. There is no output schema, but the description gives a clear mental model of the response (suggestions with thumbnails). It could specify the exact output fields, but given the context, the description is adequate.

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% for all three parameters, so the baseline is 3. The description does not add further parameter-level details, but the schema already documents what q, shop_id, and store_slug mean. The tool's description does not need to compensate for any gaps.

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 tool's function: 'Search Instacart product terms at a store.' It further distinguishes itself by specifying it returns autosuggestions (term-level) rather than a paginated product-results list, which differentiates it from sibling tools like instacart_item or a general product search.

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 explicitly states the intended use case: getting Instacart's own autosuggestions for a keyword within one store. It also provides a clear exclusion: 'not a paginated product-results list,' which tells the agent what it won't return. However, it does not name alternative tools for product searches, so it falls short of a 5.

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