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Show-level listening

get_show_analytics
Read-onlyIdempotent

Get plays and listener counts for your show from Apple Podcasts Connect by day, week, or month. Track device-based audience engagement across dates or regions.

Instructions

Plays and listener counts for your show over one reporting period, from Apple Podcasts Connect. Listener counts are devices rather than people: one person listening on a phone and a speaker counts twice, and Apple has no way to collapse them. Needs Apple Podcasts Connect credentials.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNoThe reporting date, as YYYYMMDD, or YYYYMM for a Monthly report. Defaults to three days ago, because Apple publishes on a one to two day lag and asking for today reliably returns no data.
date_typeNoApple's reporting granularity. Daily and Weekly take a date as YYYYMMDD, Monthly as YYYYMM. Defaults to Daily.
worldwideNoUse the worldwide report, which drops the per-storefront breakdown and returns totals. Smaller and the right choice unless the question is about geography.
Install Server

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the bar is lower. The description adds genuine value beyond the annotations: listener counts are device-based, not unique people, and credentials are required — a material caveat that changes how an agent should interpret results. No contradiction with the annotations.

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, each earning its place: return value and source, a critical data-interpretation caveat, and a prerequisite. The purpose is front-loaded. The caveat sentence is slightly long but contains high-value information that justifies its length.

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?

With no output schema, the prose must convey what the agent will receive, and it does — plays and listener counts, scoped to one reporting period. The date-lag and default behavior live in the schema, safety in the annotations, and credentials in the description. For a read-ony analytics query with simple parameters, this is complete enough; only a structured return-shape description is missing.

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%, and the date parameter already carries rich semantics (YYYYMMDD/YYYYMM formats, the three-day default, and Apple's publishing-lag rationale). The description adds only the 'one reporting period' framing and nothing new about constraints or formats, so the schema does the heavy lifting. Baseline 3 is appropriate.

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 states a specific resource and scope: 'Plays and listener counts for your show over one reporting period, from Apple Podcasts Connect.' The title 'Show-level listening' and the phrase 'your show' distinguish this from episode-level analytics tools like get_episode_analytics. It doesn't explicitly name a sibling or state what it is not, so it stops short of 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 Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The context for when to use it is implied: show-level listening metrics from Apple Podcasts Connect, with the prerequisite spelled out ('Needs Apple Podcasts Connect credentials'). However, with 24 siblings including easily confused tools like get_episode_analytics and get_analytics_report, there is no explicit routing guidance or mention of alternatives.

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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