instacart_search_nearby

Does 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 disclose that the tool returns autosuggestions, aggregates across retailers, and uses public data, which implies a safe read operation. However, it omits details about authentication, rate limits, or response structure beyond 'suggestions,' leaving some behavioral uncertainty.

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 short and front-loaded with the core purpose. The third sentence ('Public data sourced from Instacart's own cross-retailer search') adds useful public-data context but is somewhat redundant with the second sentence's emphasis on cross-retailer search, so it is not maximally taut.

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 two-parameter tool with no output schema, the description is reasonably complete: it states the input context, the result type ('autosuggestions'), and the scope (all retailers near a postal code). It lacks explicit named alternatives and response format details, but for this search tool the information provided is sufficient for basic invocation.

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%, so the parameters are already documented with clear descriptions ('Free-text search term' and 'US postal/ZIP code'). The description adds only modest context by calling q a 'keyword' and tying both parameters to the cross-retailer autosuggestion behavior, but it does not substantially enhance the schema's parameter semantics.

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 has a specific verb and resource: 'Search Instacart product terms near a postal code.' It further distinguishes itself by clarifying that it returns 'search-term autosuggestions' across every retailer rather than one specific store, which separates it from sibling tools like instacart_search or instacart_stores.

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 clearly implies when to use this tool: when you want autosuggestions aggregated across all retailers near a postal code. It explicitly contrasts with 'one specific store,' but it does not name an alternative tool such as instacart_search, so the guidance is clear but not fully explicit about alternatives.

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