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Get channel analytics

get_channel_analytics
Read-onlyIdempotent

Retrieve watch time, average view duration, retention, traffic sources, and subscriber changes for a connected YouTube channel. Requires OAuth access to the channel owner's account; data lags about two days.

Instructions

Watch time, average view duration, retention percentage, traffic sources and subscriber change for a connected channel. There is no API-key path to this data: it needs OAuth on the channel that owns it, and it exists for no one else's channel. Data lags roughly two days behind real time.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoe.g. `-views` for descending
accountNoWhich connected channel to act on (name or @handle). Required when more than one is connected: without it the call fails and lists the choices rather than picking one.
filtersNoe.g. `video==VIDEO_ID` or `country==US`
metricsNoComma-separated. Default: views,estimatedMinutesWatched,averageViewDuration,averageViewPercentage,subscribersGained,subscribersLost
end_dateYesYYYY-MM-DD
dimensionsNoe.g. `day`, `video`, `country`, `insightTrafficSourceType`
start_dateYesYYYY-MM-DD
max_resultsNo
Install Server

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already establish read-only/idempotent/non-destructive behavior. The description adds meaningful traits not in structured metadata: OAuth ownership requirement, unavailability via API key, and roughly two-day data lag. No contradiction with annotations.

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 sentences, each carrying distinct value: output scope, auth constraint, and latency caveat. No filler and the most useful identifying details are front-loaded.

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?

Covers the critical operational constraints (OAuth, ownership, lag) and the returned metrics, with schema covering parameter usage. Lacks an explicit return-shape/pagination note, and there is no output schema to fill that gap, so it is strong but not 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 description coverage is 88%, so the schema already documents the parameters and the description does not need to repeat them. The description adds no new parameter-level detail beyond implying metrics/dimensions; baseline 3 is appropriate.

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 precise resource ('a connected channel') and the exact analytics fields it returns (watch time, average view duration, retention, traffic sources, subscriber change). The ownership qualifier ('exists for no one else's channel') distinguishes it from channel lookup/sibling tools without opening schemas.

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?

Gives clear invocation context: requires OAuth on the owning channel, cannot be used with an API key, and only works for the owner's own channel. It does not explicitly name sibling alternatives (e.g., analyze_channel), so it falls a point short of full when/when-not guidance.

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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