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create_playlist_from_tracks

Creates a Spotify playlist from proposed tracks, searches each on Spotify, adds confident matches, and returns the playlist ID while listing any unresolved tracks.

Instructions

Create a playlist from LLM-proposed {title, artist} picks. The server searches each on Spotify, adds the confident matches, and reports any it couldn't find under 'unresolved'. Returns the new playlist_id + uri.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
publicNo
tracksYes
descriptionNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It explains that the server searches, adds only confident matches, reports unresolved items, and returns playlist_id + uri. This is materially useful, though it leaves details like auth requirements and the definition of 'confident' unspecified.

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?

The description is three tight sentences: what it does, how it behaves, and what it returns. Every sentence adds information and the most important purpose is 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?

For a create-style tool with no annotations and four parameters, the description covers the core workflow, the partial-resolution behavior, and the return value. It lacks details about optional parameters and edge cases, but the main agent decision path is well supported.

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 coverage is 0%, so the description must compensate. It adds meaning for 'tracks' by specifying each entry is a {title, artist} pair, and 'name' is implied by 'Create a playlist'. However, the 'public' and 'description' parameters are not mentioned, leaving some semantics uncovered.

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 clearly states the verb ('Create'), the resource ('playlist'), and the distinguishing input ('LLM-proposed {title, artist} picks'). It also reveals the search-and-add workflow, which separates it from siblings like append_to_playlist or resolve_tracks.

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 implies a clear use case: when you have title/artist pairs and want a new playlist created from them. It does not explicitly contrast with siblings like resolve_tracks or append_to_playlist, but the described behavior is distinctive enough for an agent to select it appropriately.

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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