Search Salvage & Surplus product catalog. Returns matching GPU rigs, server racks, drive arrays, and network gear. Filter by category: compute, servers, storage, networking, support.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| category | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It does add value by specifying result categories and filter options, but it omits details such as read-only nature, pagination behavior, or any prerequisites. The behavior is mostly transparent, but not fully disclosed.
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 short sentences, each delivering distinct information: what the tool does, what it returns, and how to filter. No filler or redundancy, making it easy for an agent to parse quickly.
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 its simplicity (2 params, output schema present), the description is mostly complete. It covers purpose, results, and filters. It does not mention pagination or sorting, but these are often standard and may be inferred from the output schema. For a search tool, this is adequate.
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 0%, so the description must compensate. It explains the category parameter by listing allowed values (compute, servers, storage, networking, support), which is helpful. However, the query parameter is not elaborated (e.g., what fields it searches, matching rules), leaving partial semantic coverage.
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 opens with 'Search Salvage & Surplus product catalog', a specific verb-resource pair. It then lists concrete result types (GPU rigs, server racks, drive arrays, network gear) and filter categories, which clearly differentiates it from siblings like get_product, add_to_cart, and checkout.
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 usage is implied (search to find catalog items, optionally filter by category), but there is no explicit 'when to use this vs. get_product' or any exclusion criteria. The description does not reference siblings, so guidance is inferred rather than stated.
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 distinct role: product discovery (search_products, get_product), cart management (add_to_cart), and payment processing (checkout, confirm_payment). The sequential flow is clear and there is no overlap between tools.
Most tools follow a consistent lowercase verb_noun pattern (add_to_cart, confirm_payment, get_product, search_products). 'checkout' deviates slightly as a single verb, but it is still clear and follows the same overall style.
With 5 tools, the server is well-scoped for a simple purchase workflow. Each tool is necessary for the core flow of searching, viewing, adding to cart, and completing a purchase.
The purchase lifecycle is covered end-to-end: search, retrieve details, add to cart, checkout, and confirm payment. Minor gaps exist such as no update/remove cart functionality, but these do not block the primary workflow.