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Glama

Influship Influencer Marketing MCP

Get YouTube channel

get_youtube_channel
Read-only

Fetch a current YouTube channel by handle, channel ID, or URL.

Optionally includes recent videos. This is a metered live-data request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
channelYesA handle, channel ID, or YouTube channel URL.
video_limitNo
include_videosNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
dataNo
countNo
resultsNo
has_moreNo
not_foundNo
next_cursorNo
suggested_followupsNo

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds non-obvious behavioral context: the call is 'metered' and returns 'live' data, which implies potential cost and that results reflect the current state of YouTube. This goes beyond the annotations without contradicting them.

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 short, purposeful sentences: what the tool fetches and how, the optional video behavior, and the metered live-data warning. The most important information is front-loaded, and there is no filler or repetition of schema details.

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 output schema exists and annotations cover the read-only, non-destructive safety profile, the description is largely complete. The channel parameter is fully covered in the schema, and the metered live-data warning covers the key caveat. The only small gap is the undefined interaction between include_videos and video_limit, but defaults in the schema mitigate this.

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

Parameters2/5

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

Schema description coverage is only 33%, so the prose needed to compensate for the undocumented video_limit and include_videos parameters. The phrase 'Optionally includes recent videos' partially clarifies include_videos, but video_limit is never explained in the description, and its semantics are left entirely to the parameter name and constraints. This is a meaningful gap at 33% coverage.

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?

The description uses a specific verb ('Fetch'), names the exact resource ('YouTube channel'), and lists the supported identifier forms ('handle, channel ID, or URL'). The word 'current' distinguishes this from historical or cached lookups, and the YouTube-specific resource clearly separates it from siblings like get_creator, get_profile, or get_youtube_video.

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 makes clear when to call it: to fetch a current single YouTube channel by handle/ID/URL, with optional recent videos. It also flags that it is a 'metered live-data request,' giving cost/latency context. It does not explicitly name alternatives or exclusions, but the resource and identifier criteria are enough to route an agent appropriately.

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

A3.8/5.0
Disambiguation2/5

Several tools have overlapping boundaries: autocomplete_creators and search_creators are described as near-equivalent fuzzy lookups, get_creator and get_profile both resolve exact platform+username input, and the Instagram/TikTok post helpers overlap with generic get_posts. The descriptions work hard to disambiguate, but an agent would frequently need to choose between two or three equally plausible tools.

Naming Consistency4/5

Most tools follow a clear verb_noun snake_case pattern, such as get_youtube_video, search_creators, match_creators, and render_creator_profile. Minor inconsistencies exist: singular/plural variants (get_instagram_post vs get_instagram_posts), list_ vs get_ for video listing, and search_creators carrying legacy semantic behavior under a lookup-sounding name.

Tool Count2/5

Twenty-eight tools places the server in the 'too many' range, and the count is inflated by near-duplicates like autocomplete_creators/search_creators, get_creator/get_profile, and singular/batch transcript variants. Even with three social platforms and rendering helpers, the surface would be more focused around 18–22 tools.

Completeness4/5

The core influencer research workflow is well covered: handle resolution, batch lookup, semantic discovery, lookalikes, posts, transcripts, YouTube search, matching, and comparison rendering. Gaps are minor—there is no creator shortlist persistence or cross-platform comment support—but the main discovery-to-match path has no dead ends.

Resources