Find the cheapest option for a product across all Australian grocery retailers. Searches by name and returns results sorted by price ascending.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Number of results (1-50, default 10) | |
| product_name | Yes | Product to search for (e.g., 'full cream milk 2L') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the search scope ('across all Australian grocery retailers') and result ordering ('sorted by price ascending'), which adds behavioral context beyond the schema. However, it does not mention whether the operation is read-only or any other edge-case behaviors, leaving some gaps.
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 two concise sentences with no redundancy. It front-loads the core purpose and includes the most important detail (price sorting) efficiently.
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 search tool, the description adequately covers the essential behavior: search by name, national scope, and price sorting. It does not detail the return format, but given the simplicity and lack of output schema, this is a minor omission. The description is complete enough for an agent to select and invoke the tool correctly.
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%: both product_name and limit are clearly described in the schema. The description does not add additional parameter semantics beyond reinforcing that the search is by name, so the baseline of 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 clearly states the tool's specific function: finding the cheapest option for a product across Australian grocery retailers. It uses a specific verb ('Find') and resource ('cheapest option'), and explicitly mentions sorting by price ascending, which distinguishes it from generic search tools.
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 implies usage when the user needs the lowest price across all Australian retailers, but it does not explicitly contrast with sibling tools like compare_prices or search_products. There is no direct 'when not to use' guidance, but the purpose is clear enough to infer appropriate scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct roles with explicit workflow guidance, but search_products and get_cheapest overlap in purpose (both search by name and return price data), and batch_search vs search_products could be confused without careful reading. The detailed descriptions mitigate this but don't eliminate it.
Tool names are consistently snake_case, mostly verb_noun or get_noun. batch_search is a minor deviation (noun+verb) but still readable and consistent with the style.
10 tools is well-scoped for a grocery price comparison server, covering search, details, history, specials, and basket management without excessive redundancy.
The server covers the core domain well: product search, price comparison, history, specials, and basket building/saving. Minor gaps include no way to fetch a saved basket programmatically and no explicit basket editing, but these can be worked around.