Skip to main content
Glama

youtube_channel_shorts

Channel Shorts with cursor pagination — same row shape as channel-videos (exact publishedAt). 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
urlYesYouTube channel URL, @handle, bare handle, or UC... channel ID, e.g. https://youtube.com/@handle or @mkbhd. 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 200). Flat 2 credits per call.
cursorNoPagination cursor. Leave empty for the first page; then pass the nextCursor value returned in the previous response.

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well: it discloses cursor pagination, output row shape equivalence, exact publishedAt behavior, the 2-credit cost, that empty results and failures are never charged, and cache semantics. This goes well beyond minimal disclosure, though it stops short of mentioning rate limits or auth requirements, which would be expected for full transparency.

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 sentences with no filler: the first states the core function and row-shape guarantee, the second covers cost and failure policy, the third explains cache behavior. All information is relevant and front-loaded, with the most distinguishing detail (channel-videos row shape) placed early.

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?

The description covers pagination, cost, cache, failure policy, and output shape via a pointer to channel-videos. Since there is no output schema, the row-shape reference is helpful but assumes knowledge of the sibling tool's return fields. For a small-parameter list tool, this is nearly complete, though a couple of example output fields would fully close the gap.

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. The description adds context about cursor pagination and cost, but those are also reflected in the schema's parameter descriptions (cache, cursor). It does not add new parameter-level semantics beyond what the schema already provides, so the baseline holds.

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 ('Channel Shorts') and key capability (cursor pagination), and references 'same row shape as channel-videos' to hint at sibling differentiation. However, it lacks an explicit verb like 'List' or 'Fetch,' relying on the tool name and noun phrase to convey action. It is clear enough to distinguish from channel-videos, streams, and playlists, but not as explicit as it could be.

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 mention of 'same row shape as channel-videos' implies a relationship to that sibling tool, and 'Channel Shorts' signals when to use it, but the description never explicitly states 'use this for shorts, channel-videos for regular videos' or names exclusions. Usage context around pagination, credits, and caching is provided, so the agent gets some guidance but must infer the selection rule.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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.