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youtube_shorts_summarize

AI summary of a YouTube Short — rejects long-form videos (≤3 min only). Costs 3 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
urlYesPublic YouTube Shorts URL, e.g. https://youtube.com/shorts/ID (≤3 min). Long-form videos return HTTP 422 — use the matching /v1/youtube/… endpoint instead. 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.
languageNoPreferred caption language as an ISO code, e.g. "en". Defaults to auto-detect.

TDQS

A4.4/5.0
Behavior5/5

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

With no annotations at all, the description carries the full burden and delivers: pricing ('Costs 3 credits'), failure-charge policy ('Empty results and failures are never charged'), and caching semantics ('cache=true for a free 24h cache hit (default always fresh)'). These are exactly the non-obvious behavioral traits an agent needs to predict the cost and side effects of an invocation.

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?

Three tight sentences with zero filler: purpose is front-loaded, constraints and cost follow immediately, then cache guidance. Every clause 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 simple 3-param tool with no annotations and no output schema, the description covers purpose, input constraints, cost, failure policy, and cache behavior — all needed for correct invocation. The only gap is that the returned summary's format or verbosity is never described, which is notable given there is no output schema to fill that in.

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 and the schema already fully documents url, cache, and language. The description's mention of cache=true and the credit cost is largely redundant with the schema's own '0 credits on hit' note, adding marginal but non-essential value.

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?

States a specific verb and resource ('AI summary of a YouTube Short') and immediately adds the defining scope constraint ('rejects long-form videos ≤3 min only'). This clearly separates it from youtube_summarize/video_summarize and other platform summarize siblings even before the schema's 422 note is read.

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?

The description gives clear context for when to use the tool (Shorts only, ≤3 min) and the schema explicitly warns 'Long-form videos return HTTP 422 — use the matching /v1/youtube/… endpoint instead' and cautions against cross-platform URLs. However, the alternative endpoint is referenced generically rather than naming the sibling tool (youtube_summarize), so an agent must infer which sibling that is.

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.