google_adLibrary_advertisers_searchSearch Google Ad Transparency advertisers by name. Accepts a advertiser name. Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query text for Google Ad Transparency advertisers. | |
| region | No | Two-letter country code to search in. Default: `US`. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the description's safety profile is covered. It adds the important behavioral detail that the result is a list and that pagination uses a cursor, which is beyond what annotations or the schema provide. This is genuinely useful context for an agent.
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 short sentences, front-loaded with the primary action. It includes a useful note about cursor pagination without any fluff. Every sentence earns its place, and the length is appropriate for the tool's complexity.
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 lack of an output schema, the description does mention the return is a list and cursor-based pagination, which is helpful. It covers the main functional aspects. It could potentially detail what fields are returned, but for a simple search tool with well-defined parameters, it is reasonably 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?
Schema coverage is 100%—both query and region have descriptions in the schema. The description repeats that it accepts an advertiser name, which does not add meaningful value beyond the schema. However, it does not introduce any conflicting or confusing parameter info, so it meets the baseline for high 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 clearly specifies the action (search), the resource (Google Ad Transparency advertisers), and the criterion (by name). It also notes the return type (list) and pagination approach, distinguishing it from siblings like google_adLibrary_ad_get and google_company_ads_list which have different purposes.
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 states that it accepts an advertiser name, implying a use case, but does not explicitly contrast with alternative tools or provide when-to-use/when-not-to-use guidance. It lacks explicit exclusionary language that would help an agent decide between this and similar search tools in the sibling list.
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 is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.
All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).
The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.
The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.