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itunes_dislike_track

Adjust the current track's rating in Apple Music to influence recommendations. Set disliked to true to ban a track, or false to remove the dislike.

Instructions

Mark or un-mark the currently playing track as Disliked for recommendation algorithms.

Args: disliked: True to dislike/ban the track, False to remove dislike.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dislikedNo
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so well. It explicitly discloses that this is a state-changing operation (mark/un-mark), clarifies both states of the 'disliked' flag, and applies only to the currently playing track. It doesn't address error conditions or idempotency, but for a simple boolean setter, this is solid.

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 tightly-constructed sentences cover the tool's purpose and parameter semantics without a single wasted word. The Args section is a clean, minimal format that informs an agent at a glance. Every sentence earns its place.

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?

For a simple 1-boolean-parameter tool with no complex output, this description covers the essentials: what it does, on what scope, for what impact, and how the parameter maps to behavior. Minor gaps include no note on error states (e.g., no track currently playing) or reversibility, but for a tool this simple, the description is near-complete.

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

Parameters5/5

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

Schema description coverage is 0%, meaning the description must fully explain the 'disliked' parameter, and it does. 'True to dislike/ban the track, False to remove dislike' adds crucial semantic weight — including the 'ban' synonym — that the bare boolean schema field 'Disliked' completely lacks. The description perfectly compensates for the 0% schema 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 begins with 'Mark or un-mark the currently playing track as Disliked' — a specific verb and resource that clearly distinguishes this from sibling tools like itunes_favorite_track and itunes_rate_track. The purpose ('for recommendation algorithms') adds valuable context about the tool's effect.

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 provides clear scope by stating it operates on the 'currently playing track' and clarifies the functional effect ('for recommendation algorithms'). However, it doesn't explicitly contrast with alternatives like itunes_favorite_track, and there's no mention of preconditions (e.g., what happens if no track is playing). Clear context, but no explicit exclusions.

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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