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Search LinkedIn Ad Library ads

linkedin_adLibrary_ads_search_list
Read-only

Search LinkedIn Ad Library ads by company, keyword, or company id. Returns a list (use cursor when paginated).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cursorNoOpaque pagination cursor from a previous response.
companyNoCompany name to search for in the LinkedIn Ad Library.
endDateNoOptional end date filter in YYYY-MM-DD format.
keywordNoKeyword or phrase to search for in LinkedIn Ad Library ads.
companyIdNoLinkedIn company id to search for in the Ad Library.
countriesNoOptional comma-separated list of country codes (for example US,CA,MX).
startDateNoOptional start date filter in YYYY-MM-DD format.

TDQS

A4/5.0
Behavior4/5

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 addition of pagination behavior (use cursor when paginated) and the return type (list) provides extra context beyond the annotations. It does not contradict the annotations and offers a useful hint about handling paginated results, though it could disclose more about potential data limits or freshness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded: the first sentence states the tool's purpose and search dimensions, while the second covers the return type and pagination. Every word earns its place, with no filler or repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the moderate complexity (7 optional parameters, no output schema), the description covers the essential aspects: what it searches, how to paginate, and that it returns a list. It doesn't explain parameter interactions or constraints (e.g., whether at least one search criterion is needed), nor does it detail the return fields. However, since the schema fully documents parameters and annotations cover read-only safety, the description is largely sufficient for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so all parameters are already detailed in the schema. The description adds minimal value by restating the search criteria (company, keyword, company id) that the schema already explains. The cursor hint is redundant with the schema's 'Opaque pagination cursor from a previous response.' No significant new semantic information is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches LinkedIn Ad Library ads and specifies three distinct search criteria (company, keyword, company id). It distinguishes itself from the sibling linkedin_adLibrary_ad_get (which likely retrieves a single ad) and from other platforms' ad search tools. The return type (list) and cursor mention further clarify its function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool versus alternatives, such as the singular ad get tool or other platform-specific ad searches. It implies usage through the search criteria but offers no exclusions or conditions. For instance, it doesn't say 'use this when searching across ads' or 'use ad_get to retrieve a specific ad.' Guidance is implicit rather than explicit.

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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TDQS

B3.4/5.0
Disambiguation5/5

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.

Naming Consistency5/5

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.).

Tool Count2/5

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.

Completeness4/5

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.