Compare prices for the same product across retailers using its barcode. Returns all retailers stocking the product, sorted cheapest first. About 7,800 products have barcode matches.
| Name | Required | Description | Default |
|---|---|---|---|
| barcode | Yes | EAN-13 barcode (e.g., '9300675016902') |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the return format (all retailers sorted cheapest first) and adds a non-obvious limitation ('about 7,800 products have barcode matches'). This helps set expectations about potential empty results, but it does not mention edge cases like unavailable prices or data freshness.
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, followed by output behavior and a caveat. No wasted words; each sentence earns its place.
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 the tool's simplicity (one parameter, no output schema), the description is largely complete: it states the action, the input method, the output format, and a key limitation. It lacks explicit alternative guidance, but that is partially covered by purpose clarity. Overall, an agent has enough to select and invoke it 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?
The schema already describes the single parameter (barcode) fully, so the baseline is 3. The description adds value by explaining the product coverage limitation ('about 7,800 products have barcode matches'), giving users context about expected match rates beyond the schema.
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: compare prices for the same product across retailers using a barcode. It also specifies the output (returns all retailers, sorted cheapest first), which distinguishes it from sibling tools like get_cheapest or get_price_history.
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 you need to compare prices across retailers for a specific product), but it does not explicitly mention when to use this tool versus alternatives like get_cheapest or get_product. No exclusions or alternative tool names are given, so guidance is only implicit.
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.