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List a channel's latest posts

list_channel_stats
Read-onlyIdempotent

List the latest posts of a YouTube channel with the view count its public channel page shows, newest Shorts first, then videos. For a TikTok profile it returns followers, total likes and video count (TikTok's public profile page lists no videos). X timelines need a login, so an X profile is refused with the reason.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMost recent posts to return. Default 20.
channelYesA YouTube channel ("https://www.youtube.com/@handle") or a TikTok profile ("https://www.tiktok.com/@user").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNo
notesNo
postsNo
statusYes
totalsNo
channelYes
from_cacheNo
totals_sourcesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, non-destructive, open-world behavior, so the safety profile is covered. The description adds real behavioral value beyond that: result ordering (newest Shorts first, then videos), that the view count is the public channel page figure, that TikTok returns aggregate profile stats instead of posts, and that X requests fail with a reason. Rate limits and auth requirements are unstated, but the X refusal covers the main auth-related edge case.

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?

Three sentences, front-loaded with the primary YouTube behavior before the platform exceptions, and every sentence carries distinct information (ordering, TikTok payload, X refusal). The first sentence is clause-heavy but not padded.

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?

An output schema exists, so return-value explanation is optional, yet the description still usefully characterizes the shape of results per platform. Combined with full schema coverage and clear annotations, an agent has enough to call this correctly; only the absence of sibling routing and rate-limit/auth detail keeps it from a 5.

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 both parameters are already documented, including the accepted channel URL formats and the limit default of 20. The description adds no parameter-level detail (it never mentions limit or URL format beyond what the schema states), so the baseline 3 applies.

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 names a specific verb and resource ('List the latest posts of a YouTube channel') and immediately scopes it by platform, so an agent knows exactly what data comes back for YouTube vs TikTok vs X. It does not explicitly distinguish itself from siblings like get_post_stats or compare_posts, which is the only thing keeping this from a 5.

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?

It gives usable context: works for YouTube channels and TikTok profiles, and X profiles are refused because timelines need a login. That is a concrete when-not condition. However, no alternative tool is named for the post-level or comparison cases, so routing among siblings is left implicit.

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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