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remove_from_library

Remove tracks, albums, episodes, shows, audiobooks, users, or playlists from your Spotify library in one request. Use dry-run to preview exact removals before applying.

Instructions

Preferred. Accepts the widest URI mix (track, album, episode, show, audiobook, user, playlist) in one request. Remove one or more items from the user's library via Spotify's unified library endpoint. Max 40. Set dry_run=true to preview.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urisYesSpotify URIs to remove
dry_runNoPreview only: show exactly which URIs would be removed without calling the API
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It clearly states the destructive nature ('Remove'), the maximum batch size (40), and the dry_run preview option. However, it does not mention irreversibility, authentication requirements, or what happens after successful removal, which would be valuable for a mutation tool.

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?

Four short sentences carry all key decision information up front: preference, accepted input breadth, action, limit, and preview capability. There is no filler or redundant restatement of the tool name.

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 mutation tool with no annotations and no output schema, the description gives the essential operational details: what it removes, which URI types are supported, the batch limit, and a safe preview path. It could add response/error expectations, but the core call guidance is sufficiently complete.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds genuine semantic value by enumerating the accepted URI types (track, album, episode, show, audiobook, user, playlist) that the schema's generic 'Spotify URIs to remove' does not convey. It also reinforces the max-40 limit and dry_run preview behavior.

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 states the action ('Remove one or more items from the user's library') and identifies the specific unified library endpoint. It also signals relative scope with 'widest URI mix' and lists accepted item types, which helps distinguish it from sibling removal tools like remove_saved_items.

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?

'Preferred' and 'widest URI mix' communicate when this tool should be selected over more narrow removal tools, and 'Set dry_run=true to preview' gives a concrete safe-usage pattern. It does not name alternative tools explicitly or state when not to use it, but the usage context is clear.

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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