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twitch_user_videos

Twitch channel VODs — lean rows, video-id cursor, filter/sort, top-level broadcaster{} (flat 2). 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
urlYesTwitch channel URL or username, e.g. https://www.twitch.tv/shroud. 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 items to return (default 20, max 100). Flat 2 credits per call. Hard ceiling: first 100 matching videos only — deeper history is not available (windowMax=100).
cursorNoPagination cursor = last video id from the previous nextCursor. Leave empty for the first page. Pages the first 100 matching videos only (not a raw offset).
sortByNoTIME (default, newest first) or VIEWS.
filterByNoARCHIVE | HIGHLIGHT | UPLOAD. Omit for all types — there is no default filter (unset filterBy is omitted, not null).

TDQS

A4/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so well: it discloses credit costs, free cache hits, no charge for empty/failed results, default fresh behavior, pagination style, and row shape. It also signals that this is a read-style listing operation without destructive side effects. This is substantial behavioral context beyond 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.

Conciseness5/5

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

The description is compact and information-dense, with the most important facts front-loaded. Every clause provides useful operational information, and there is no filler or redundant restating of the tool name. The two-sentence structure is easy for an agent to parse.

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 rich input schema and lack of an output schema, the description covers the main operational concerns: scope, pagination, filtering, sorting, cost, caching, and failure behavior. It does not detail response fields beyond 'lean rows' and the broadcaster object shape, but this is sufficient for an agent to select and invoke the tool. A little more explicit output-structure guidance would make it fully complete.

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%, and each parameter already has detailed descriptions, so the baseline is 3. The description adds some related context ('video-id cursor, filter/sort, top-level broadcaster{}') but mostly restates or hints at what the schema already documents. It does not meaningfully compensate for any missing parameter-level semantics.

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 clearly identifies the resource as 'Twitch channel VODs' and conveys that this endpoint returns video rows with filtering and sorting. It does not use an explicit verb like 'list' or 'fetch', but the 'lean rows, video-id cursor, filter/sort' phrasing makes the operation unambiguous. The name plus 'Twitch channel VODs' differentiates it from sibling tools like twitch_clip and twitch_user_schedule.

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 resource statement 'Twitch channel VODs' implies when to use this tool, and the schema warns against cross-platform URLs. However, the description does not explicitly state when to use this tool instead of related Twitch siblings or other channel-video tools. The guidance is mostly inferred from the resource name rather than stated.

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.