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tiktok_popular_creators

Creative Center creators + createTime / bioLinkRisk / ttSeller hydrate for partnership vetting. Costs 2 credits. Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoCreative Center page (default 1).
sortNofollower, engagement, or popularity. Default follower.
cacheNoSet true to serve from the response cache (default TTL). Default false — always fetch fresh. Prefer cacheMaxAge when you need 1d–30d freshness control.
limitNoMax items to return (default 20, max 100). Flat 2 credits per call.
countryNoTwo-letter ISO country code. Default US.
cacheMaxAgeNoMax age of a cached response: 1d, 3d, 7d, 14d, or 30d. When set, enables caching with that TTL.
follower_countNoOptional range on FYP/Apify fallthrough: 10k-100k, 100k-1m, 1m-10m, >10m.

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden and does real work: it discloses the flat 2-credit cost, guarantees empty results and failures are never charged, and specifies the default always-fresh behavior plus the free 24h cache=true path. It omits rate limits and auth, but for a non-destructive read tool the cost/caching/failure policy is the core disclosure an agent needs. Nothing in the description contradicts the schema.

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

Conciseness4/5

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

Four short sentences, each carrying a distinct fact: purpose, cost, charge-on-failure policy, and caching default. The purpose is front-loaded and there is no filler, but the telegraphic style ('Creative Center creators + ... hydrate') reads as jargon and slightly obscures the primary action.

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

Completeness3/5

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

With no output schema present, the description should hint at the return contract; it lists only three hydration fields and never describes the response shape, creator fields, or pagination behavior. The operational essentials (cost, caching, failure policy) and all parameters are covered, so the definition is adequate but leaves the result format to the agent's imagination.

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 the baseline is 3; all seven parameters are already documented, including the cache/cacheMaxAge relationship and the follower_count FYP/Apify fallthrough. The description adds only marginal parameter nuance — that cache=true is free and yields a 24h hit — without adding meaning to the other six parameters.

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

Purpose4/5

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

The description identifies a specific resource (Creative Center creators), the enriched fields (createTime, bioLinkRisk, ttSeller), and a concrete use case (partnership vetting), which helps distinguish it from siblings like tiktok_search_users and tiktok_trending_feed. However, it never states an explicit verb such as 'list' or 'fetch,' and 'hydrate' is unexplained jargon, so the primary action is only implied by the tool name.

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 'for partnership vetting' clause provides use-case context that implies when the tool should be used, and the cache=true advice is practical call-time guidance. But there is no explicit routing against sibling tools, no when-not-to-use condition, and no mention of how this relates to alternatives like tiktok_search_users or tiktok_channel_details.

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

B3.2/5.0
Disambiguation3/5

The platform-prefix convention keeps most of the 178 tools clearly separated, but several clusters are genuinely ambiguous: tiktok_live_info is explicitly described as 'Identical to TikTok Live', instagram_basic_profile and instagram_channel_details both return profile stats, and facebook_profile_posts overlaps with facebook_profile_reels. The generic 'Summarizer' descriptions for facebook_summarize, instagram_summarize, and tiktok_summarize provide no disambiguating detail at all.

Naming Consistency4/5

The dominant snake_case platform_resource_suffix pattern is followed remarkably consistently across 178 tools (e.g. youtube_channel_videos, tiktok_search_users, reddit_subreddit_posts). Minor deviations exist: the same creator resource is called 'channel' in some tools (tiktok_channel_details, instagram_channel_posts) but 'profile' or 'user' in others (facebook_profile_posts, twitch_user_videos, linnkme_profile); link-in-bio tools mostly use _page but linkme uses _profile; and the video_summarize/video_transcript pair lacks a platform prefix.

Tool Count2/5

At 178 tools this is far beyond what any agent can efficiently navigate in a single flat namespace, and even individual platform subsets exceed reasonable bounds (TikTok alone has ~34 tools, YouTube ~25). The sheer breadth of the multi-platform scope partially justifies the count, but the server would be far more usable split into per-platform servers.

Completeness4/5

The read-only data surface is impressively thorough: nearly every platform has profile + content + search + comments coverage, and TikTok, YouTube, Instagram, and Facebook are covered end-to-end including shops, ads, transcripts, and summaries. Notable gaps are minor: Twitter has no keyword search tool, LinkedIn lacks comments, and Reddit has no user-profile endpoint, but none of these create dead ends for the server's core data-retrieval purpose.