| Name | Required | Description | Default |
|---|---|---|---|
| geo | No | ISO 3166-1 alpha-2 country code | |
| brand | No | Filter by brand name | |
| query | Yes | Natural language product query | |
| category | No | Filter by product category | |
| max_results | No | Maximum results (1-50, default: 10) | |
| budget_max_cents | No | Maximum budget in cents |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety profile is clear. The description adds that this tool delegates to nexbid_search internally, which is useful behavioral context. It also describes the output format (product list fields), going slightly beyond the minimum.
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 split into short, focused sections (tool_description, when_to_use, combination_hints, output_format) with no filler. Every sentence provides value, and the most critical information (what it does and when to use) is front-loaded.
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 the tool's simplicity (a read-only alias with six well-documented parameters and no output schema), the description is complete. It includes purpose, usage guidance, combination hints, and even specifies the output format fields, leaving no obvious gaps for an AI agent to infer.
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 100%, so the schema fully documents all six parameters. The description adds no extra parameter-specific meaning, but it does hint at the query semantics via 'product query' and output fields. Baseline of 3 is appropriate since schema carries the burden.
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 'Search for products in the Nexbid marketplace' with a clear verb and resource, and explicitly identifies itself as an alias for nexbid_search with content_type='product'. This distinguishes it from sibling tools like nexbid_search and get_product.
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 'when_to_use' section explicitly states when to use this tool ('When an agent needs to discover products') and what not to use it for ('not recipes or services'). It also provides an alternative by saying to use nexbid_search with content_type filter for those cases, satisfying the when/when-not/alternatives requirement.
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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Most tools have distinct purposes, but there is some overlap between get_product and nexbid_product, which are explicitly described as aliases, and between list_products and nexbid_search with content_type='product'. This could cause confusion, though descriptions help clarify. Other tools like activate, pause, and cancel are well-differentiated for media buy lifecycle management.
The naming is mixed with no consistent pattern. Some tools use verb_noun (e.g., create_media_buy, list_inventory), others use noun_verb (e.g., nexbid_search, nexbid_purchase), and some are single verbs (e.g., activate, pause, cancel). While readable, the lack of a uniform convention across the set reduces predictability.
With 19 tools, the count is on the higher side but reasonable for the dual domains of media buying and marketplace discovery. It covers operations like listing, creating, managing, and reporting, which justifies the number. However, it borders on feeling heavy, especially with overlapping tools like get_product and nexbid_product.
The tool set provides comprehensive coverage for both media buying (create, submit, activate, pause, cancel, track, settle, report, compliance) and marketplace discovery (search, categories, product details, purchase, order status). There are no obvious gaps; workflows are well-supported with clear combination hints, ensuring agents can handle end-to-end tasks without dead ends.