search_productsLive search of 100,000+ fine-jewelry products (gold, sterling silver, NCAA/collegiate LogoArt). Returns name, SKU, live price, availability, product URL, and image. Best queries are short and specific (e.g. 'alabama pendant', '14k rope chain 20 inch').
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search terms (product type, school/team, metal, style). | |
| max_results | No | Max products to return (default 6). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, but description discloses 'live' nature, return fields, and query behavior. Does not mention rate limits or auth, but as a search tool, these are less critical. No contradictions.
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?
Two sentences with no filler. First sentence covers purpose and output; second gives guidance. 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 search tool, description explains output fields (name, SKU, price, etc.) and input constraints (max_results). No output schema needed. Could mention default results or pagination, but not essential.
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 covers both parameters with descriptions. Description adds value with query style advice ('best queries are short and specific') and examples, going beyond 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?
Clearly states 'live search of 100,000+ fine-jewelry products' with specific verb and resource. Distinguishes from siblings (get_product, get_store_policies) by focusing on multi-result search.
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?
Provides query tips ('short and specific', examples) and implies use for broad searches. Could explicitly compare to get_product for single-item lookups, but sibling names offer context.
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: product search, product detail retrieval, and store policies. No overlap or ambiguity.
All tool names follow a consistent verb_noun pattern (get_product, get_store_policies, search_products), making them predictable and easy to interpret.
3 tools is well-scoped for a product information server: search, detail, and policies. Each tool serves a necessary and distinct function without redundancy.
The tool surface covers core product discovery and policy lookup. Minor gaps exist, such as missing category or brand browsing, but the essential workflows are supported.