search_productsUse when the user names a category by keyword (e.g. 'kraft tape', 'bubble mailer', 'starter kit') with no dimensions. For dimension-based fit, prefer find_packaging_for_item. Returns products with price, stock, URL.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | Free-text search; matches title, vendor, type, tags. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint and openWorldHint, so the safety profile is covered. The description adds behavioral context by specifying that the result includes products with price, stock, and URL, which is useful since no output schema exists. It does not over-explain but provides relevant return information.
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 two sentences: the first front-loads the desired usage scenario, the second succinctly states the return contents. Every sentence earns its place without redundancy or fluff.
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 search tool with readOnly/openWorld annotations and no output schema, the description covers the key aspects: when to use, what results include, and a sibling alternative. It could mention that results might be empty or paginated, but those are minor gaps given the tool's simplicity.
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 input schema describes 'query' ('Free-text search; matches title, vendor, type, tags') and 'limit' constraints (default, min, max). The description reinforces that query is for category keywords but adds little extra meaning about parameters. With 50% schema description coverage, the description is not needed to compensate fully, and it does not mislead.
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 states a specific verb ('Search'), a resource ('products'), and the scope ('when the user names a category by keyword...'). It clearly distinguishes itself from sibling find_packaging_for_item by specifying 'with no dimensions' and pointing to that alternative for dimension-based fit.
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 declares when to use the tool ('Use when the user names a category by keyword... with no dimensions') and names the alternative for other cases ('For dimension-based fit, prefer find_packaging_for_item'). This is direct, actionable guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Several tools have overlapping purposes: check_inventory and inventory_status both focus on live stock, find_packaging_for_item and pack_calculator both handle dimension-based fitting, and create_cart_url, prepare_purchase_handoff, and get_cart_handoff_candidates all revolve around cart handoff. While descriptions add some clarity, an agent could easily select the wrong tool without careful reading.
Most tools follow a verb_noun pattern (e.g., check_inventory, get_pricing, search_products), but inventory_status and pack_calculator are noun-based and break the convention. The naming is still predictable and readable overall.
15 tools is at the upper edge of the ideal range, and the count feels slightly inflated due to overlapping inventory and cart-handoff tools. However, each tool has a defined purpose in the procurement workflow, so the count is not excessive.
The tool surface covers the full buyer journey: search, fit calculation, comparison, product detail, inventory check, pricing, cart creation, purchase handoff, shipping estimates, quotes, and reorder links. No critical dead ends were found.