| Name | Required | Description | Default |
|---|---|---|---|
| status | No | Filter by status | |
| date_to | No | Filter to date (ISO 8601) | |
| date_from | No | Filter from date (ISO 8601) | |
| max_results | No | Maximum results (default: 20) | |
| publisher_id | No | Filter by publisher UUID | |
| advertiser_id | No | Filter by advertiser UUID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description doesn't need to repeat safety. It adds behavioral context by stating the output format (ID, status, bid, budget, spent, dates) and reinforcing it's a view operation. The description aligns with annotations and does not contradict them.
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 compact, with distinct sections for what it does, when to use, combination hints, and output format. Every sentence adds value and the tool description is front-loaded with the core purpose. It avoids redundancy and is well-structured.
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 moderate complexity, the description covers purpose, usage filters, related tools, and output format. Since there is no output schema, the explicit output_format section fills that gap. The combination hints provide valuable context for multi-step workflows, making this description 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?
The input schema has 6 parameters, all with descriptions and 100% coverage. The description's mention of filtering by advertiser, publisher, status, or date mirrors the schema but adds no new semantic detail. Baseline 3 applies.
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 uses a specific verb+resource ('List media buys') and clarifies it's for viewing campaign history. It distinguishes from sibling mutation tools like create_media_buy and pause by focusing on read-only listing. The purpose is immediately clear.
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 this is for viewing existing media buys and describes filter dimensions. It also provides combination hints, directing users to get_campaign_report for performance data and get_compliance_status for compliance checks. This gives clear context for when to use this tool versus alternatives, though it doesn't explicitly state exclusions.
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.
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.