Search Australian grocery products across Woolworths, Coles, Aldi, and Harris Farm. Returns product name, price, brand, category, unit price, and whether it's on special.
| Name | Required | Description | Default |
|---|---|---|---|
| sort | No | relevance | |
| limit | No | Number of results (1-50, default 20) | |
| query | Yes | Search query (e.g., 'full cream milk', 'chicken breast') | |
| category | No | Filter by category | |
| retailer | No | ||
| on_special | No | If true, only return products on special |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses what is returned (product name, price, brand, category, unit price, on_special status) which is useful. However, it does not mention pagination behavior, data freshness, whether search is across all retailers at once, or any limitations. The description is accurate but not rich on process details.
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 sentences, concise, and front-loaded. It states the action and scope first, then the return fields. No filler 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?
Given 6 parameters, no output schema, and no annotations, the description provides a solid overview: it names the retailers and return fields, which helps an agent understand the tool's output. The schema fills in parameter descriptions. Missing are usage notes about alternatives or edge cases, but overall it is sufficiently complete for a search tool.
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 67% (4 of 6 params documented). The description adds meaning by indicating the search scope (across listed retailers) and listing return fields, which complements the schema. However, it does not clarify ambiguous params like sort or retailer beyond what the enum provides. Baseline 3 is appropriate since the schema does most of the heavy lifting.
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 Australian grocery products across Woolworths, Coles, Aldi, and Harris Farm.' It specifies the resource (grocery products) and the exact retailers, and lists return fields. This distinguishes it from siblings like get_product or get_cheapest.
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?
No explicit guidance on when to use this tool versus alternatives. It does not mention batch_search for multiple queries, compare_prices for price comparison, or get_specials for specials only. The description only implies general search capability, leaving usage context to inference.
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.