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op3_download_trend

op3_download_trend
Read-onlyIdempotent

Track podcast download trends and unique listeners over time with daily, weekly, or monthly buckets. Compare growth across halves of a selected window and identify peak periods.

Instructions

A show's downloads and unique listeners over time, bucketed by day, week or month, with a growth rate and the peak period. Growth compares the two halves of the window rather than first period against last, because podcast downloads are weekly-seasonal enough that comparing endpoints is close to noise.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endNoWindow end. Defaults to now.
botsNoInclude known bots. Off by default.
startNoWindow start, e.g. -90d, -12w, 2026-01-01. Defaults to -30d.
identifierYesAn OP3 show uuid, a podcast:guid, or the show's RSS feed URL.
granularityNoBucket size. Use week or month for windows longer than a couple of months.day
Install Server

TDQS

A4.1/5.0
Behavior5/5

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

The description discloses a non-obvious behavioral detail: growth compares the two halves of the window rather than endpoints, with the weekly-seasonality rationale. This goes beyond the readOnly/idempotent annotations and helps an agent interpret the returned growth rate correctly.

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?

Two compact sentences, with the core output front-loaded and a high-value rationale in the second. No repetitive or unnecessary wording.

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 plus the fully-covered schema and read-only annotations is sufficient for an agent to invoke the tool. It names the returned data elements, though it does not describe the exact response shape or explicitly route between sibling tools.

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

Parameters4/5

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

The schema already covers all parameters, but the description adds meaning to start/end by explaining that growth compares window halves. It also reinforces granularity semantics with the bucketing phrase, raising it above the baseline.

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 clearly identifies the resource (a show's downloads and unique listeners) and the time-series nature, also mentioning growth rate and peak period. It lacks an explicit verb, but it is specific enough to distinguish it from aggregate sibling tools like op3_show_downloads.

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 description implies use for time-series analysis of a show, and the growth explanation gives useful context, but it does not explicitly state when to prefer this over siblings or when not to use it. No alternative tools are named.

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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