find_alternatives_for_productGiven a product's EAN barcode, return every shop that carries it with prices and availability, sorted cheapest-first.
| Name | Required | Description | Default |
|---|---|---|---|
| ean | Yes | EAN barcode (8–14 digits, e.g. '4524667749493') | |
| country | No | Country for pricing (DE or AT, default DE) | DE |
| Name | Required | Description | Default |
|---|---|---|---|
| ean | Yes | ||
| alternatives | Yes | ||
| product_name | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only and idempotent behavior. The description adds that results are 'sorted cheapest-first' and includes 'prices and availability', which provides useful context beyond annotations. However, it does not detail error handling, pagination, or limitations, keeping it at a moderate level of transparency.
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 a single concise sentence that is front-loaded with the key action and context. Every word adds value, with no 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?
With a full output schema present, the description does not need to explain return values. It covers purpose, input format (EAN), and behavioral ordering (cheapest-first). The tool is simple with only 2 params, and the description covers the essential aspects adequately.
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% with good descriptions for both parameters. The description adds that the EAN is a barcode and country is for pricing, but these are restatements of schema. No additional semantic value beyond what the schema provides.
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 verb (return), resource (shops carrying a product), and sorting (cheapest-first). It distinguishes from siblings like get_best_price, which likely returns only the best price, and search_product, which may handle non-EAN queries.
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 trigger condition: 'Given a product's EAN barcode.' It implies when to use by specifying the required input. However, it does not mention when not to use or provide alternatives, leaving some room for misinterpretation.
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.
The tools 'find_alternatives_for_product' and 'get_best_price' have nearly identical descriptions, both retrieving price and availability for a product by EAN. This creates confusion and likely causes misselection. Other tools are distinct, but this overlap significantly reduces clarity.
All tool names follow a consistent verb_noun snake_case pattern (e.g., get_best_price, resolve_product, search_product). No mixing of conventions or irregular naming.
With 7 tools, the set is well-scoped for a bike parts price comparison server. Each tool serves a clear purpose in the shopping workflow, and the count is neither excessive nor insufficient.
The tool surface covers the core workflow: searching, resolving URLs, looking up by EAN, obtaining shipping info, and optimizing cart splits. The only minor gap is the redundancy between two nearly identical tools, but no essential operations are missing.