Egy adott termék részletes adatainak lekérdezése: név, ár, leírás, készlet, kép, gyártó, cikkszám.
| Name | Required | Description | Default |
|---|---|---|---|
| product_id | Yes | Termék ID (a search_products által visszaadott id mező) |
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 states the tool returns detailed data but does not disclose that it is a read-only operation, whether errors occur for invalid IDs, or any side effects. While the name implies a read, the description could be more explicit about safety and behavior.
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 sentence that conveys the purpose and key details without any unnecessary words. It is front-loaded and efficient.
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 lookup tool with one parameter and no output schema, the description adequately covers the purpose and output fields. However, it does not mention error handling or edge cases (e.g., non-existent product), which would make it more complete.
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%, and the description adds context beyond the type by stating the product_id comes from the search_products tool's 'id' field. This provides valuable integration guidance, raising the score above the baseline of 3.
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 it queries detailed data of a given product and lists the fields returned (név, ár, leírás, etc.). It distinguishes from sibling tools like search_products (which likely returns summary info) and get_categories/get_manufacturers (which handle different entities). The verb 'lekérdezése' (query) and resource 'termék' are specific.
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 does not explicitly state when to use this tool versus alternatives. It implies usage when you have a product ID and need full details, but it lacks when-not scenarios or prerequisites. The schema description mentions the ID comes from search_products, which provides a hint, but overall guidance is minimal.
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.
Each tool has a clearly distinct purpose: categories, manufacturers, product details, and search. No overlapping functionality.
All tool names follow a consistent verb_noun pattern using snake_case (e.g., get_categories, search_products).
Four tools is an appropriate scope for a read-only product catalog API, covering all essential query operations without being too many or too few.
The set covers product browsing and search well, but lacks a direct method to list all products (e.g., by category) without using search, which is a minor gap.
