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Social Fetch

by io.github.social-freak-ltd

Search TikTok Ad Library ads

tiktok_adLibrary_ads_search_get
Read-only

Search TikTok Top Ads by keyword and filters, or search the public Ads Library by advertiser name. Returns a list (use cursor when paginated).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
likesNoLikes percentile filter for Top Ads.
queryNoOptional keyword to search ad titles and content.
cursorNoOpaque pagination cursor from a previous response.
periodNoTime window in days for Top Ads.
regionNoCountry code for Top Ads results. Default: `US`.
orderByNoSort metric for Top Ads. `cvr`: conversion rate. `ctr`: click-through rate. `play-2s-rate`/`play-6s-rate`: rate viewers played past the 2s/6s mark. Default: `for-you`.
adFormatNoAd format filter for Top Ads. `spark-ads`: ads boosted from an organic creator/brand TikTok post. `non-spark-ads`: ads uploaded directly as ad creative, not boosted from an existing post.
durationNoVideo duration filter for Top Ads.
industryNoIndustry filter for Top Ads.
objectiveNoCampaign objective filter for Top Ads.
adLanguageNoAd language filter for Top Ads.
advertiserNameNoSearch the public TikTok Ads Library by advertiser name. When set, results come from the public Ads Library instead of Top Ads.

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=true, so the description doesn't need to cover safety. It adds the pagination note (use cursor) and the dual-result behavior (Top Ads vs public Ads Library), which is useful but not extensive. This is adequate given the annotation coverage.

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?

Two sentences with zero waste. The primary action is front-loaded, and the critical pagination guidance is included. Every word earns its place.

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?

For a tool with 12 optional parameters, a rich schema, and annotations covering read-only/open-world behavior, the description is sufficiently complete. It covers both search modes and pagination. It doesn't provide guidance on combining filters, but the schema descriptions for each parameter are self-explanatory. Nothing critical is missing for an agent to call it correctly.

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 coverage is 100% with descriptive text for all 12 parameters, including enums and defaults. The description only briefly mentions the cursor for pagination and the advertiserName switch, both already documented in the schema. It adds little beyond what structured data provides, so baseline 3 is appropriate.

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 states a specific verb (search) and the two resources (TikTok Top Ads by keyword/filters, and the public Ads Library by advertiser name). It clearly distinguishes from sibling tools by platform and mode, so an agent can tell it apart from other ad search tools.

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

Usage Guidelines4/5

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

It explains the two distinct usage modes (keyword/filters for Top Ads, advertiserName for the public Ads Library) and implies when each applies. However, it does not explicitly name alternatives like tiktok_adLibrary_ad_get for single-ad retrieval or other platforms' ad tools, leaving some inference to the agent.

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.

Resources