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playlist_to_library

Save all tracks from a Spotify playlist to your Liked Songs library, with optional duplicate skipping and dry-run preview.

Instructions

Save all tracks of a playlist to your Liked Songs (library). Quota: GET playlist items + PUT /me/tracks (chunked 50).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dedupeNoSkip tracks already saved (default true)
dry_runNoPreview only: validate inputs and describe exactly what would change without performing it
playlist_idYesSource playlist ID
response_formatNo'concise' = human prose, 'detailed' = more fields in prose, 'json' = raw API objectconcise

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.31.0
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
    • addedInput schema / additionalProperties
      Added value: +false
  2. Addedv1.26.1

TDQS

A3.5/5.0
Behavior4/5

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

The description adds operational context beyond the annotations: it discloses the underlying endpoints (GET playlist items and PUT /me/tracks) and chunking behavior (chunked 50). This helps the agent understand the write pattern and call volume, though it still omits auth scopes, error handling, and interaction with existing liked songs beyond what the schema's dedupe parameter implies.

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 written sentences with zero waste: the purpose is front-loaded and the quota detail follows. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a bulk library mutation surrounded by many similar siblings, the description covers what it does and the API cost, and the schema fully documents parameters. However, it omits usage guidance and sibling differentiation, which are meaningful gaps for correct tool selection in this toolset.

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%, so all four parameters (playlist_id, dedupe, dry_run, response_format) are already documented in the schema. The description adds no parameter-level meaning beyond 'all tracks,' so the baseline of 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?

States a specific verb ('Save') and resource ('all tracks of a playlist to your Liked Songs'), making the action immediately clear. It does not explicitly distinguish itself from close siblings like save_to_library, add_to_playlist, or import_playlist, so it falls 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 Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives or what prerequisites are needed. It only describes the operation itself, leaving the agent to infer routing from the name and siblings.

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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