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captapi

by io.github.CDCStream

kwai_user_posts

Kwai profile posts — caption ("" when none), engagement, mp4 + transcript (~1 credit/post). Costs ~20 credits (1/result). Empty results and failures are never charged. Pass cache=true for a free 24h cache hit (default always fresh).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesKwai profile URL or @handle, e.g. https://www.kwai.com/@topfilmeseseriesnatv. The URL platform must match this endpoint's platform. Do not pass cross-platform URLs, e.g. YouTube to TikTok, Instagram to Facebook, LinkedIn to X/Twitter, or Pinterest to Rumble.
cacheNoSet true to serve from the 24h response cache (0 credits on hit). Default false — always fetch fresh.
limitNoMax posts to return (1–200). Default 20. ~1 credit per post returned (min 2).
cursorNoOpaque pagination cursor from the previous nextCursor. Pages within posts from one profile fetch.

TDQS

A3.8/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses pricing (~1 credit/post, ~20 credits per result), the cache=true free 24h hit behavior, and that empty results/failures are never charged. It does not cover auth requirements or rate limits, but the material cost and caching behaviors are explicit and useful.

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?

The description is compact and front-loaded: purpose and output content come first, followed by cost, failure billing, and cache behavior. Every sentence adds value, though the phrase 'Costs ~20 credits (1/result)' is slightly ambiguous next to '~1 credit/post'.

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 no annotations and no output schema, the description covers the essential selection and invocation details: what posts are returned, approximate cost, cache behavior, and no-charge-on-failure policy. Pagination details come from the cursor schema, and sibling disambiguation is mostly left to the names.

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

Parameters4/5

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

The input schema already documents all four parameters at 100% coverage. The description adds operational meaning beyond the schema: cache=true gives a free 24-hour cache hit while the default is always fresh, and the credit-per-post note connects the limit parameter to cost. URL and cursor semantics are already handled by the schema.

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 the resource as Kwai profile posts and enumerates the returned content (caption, engagement, MP4, transcript), so an agent can see what the tool produces. It lacks an explicit verb such as 'list' or 'fetch' and does not distinguish itself from siblings like kwai_post or other platform user_posts, but the platform and resource scope are clear.

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?

Use is implied: this is the tool for posts from a Kwai profile, based on the name and first line. There is no explicit guidance about when to choose kwai_user_posts over kwai_post, kwai_profile, or other user_posts tools, so the agent must infer routing.

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.

Resources