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playlist_to_library

Move every track from a Spotify playlist into your Liked Songs library. Optionally skip tracks already saved or preview changes before applying.

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
Behavior3/5

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

With no annotations provided, the description carries the full burden. It does disclose meaningful behavior beyond the verb 'save': the quota cost (🟢), the underlying API calls (GET playlist items + PUT /me/tracks), and the chunked-50 batching behavior. However, it omits details an agent might need, such as reversibility, what happens on partial failure, or what the tool returns, since there is no output schema.

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 sentences with zero wasted words. The core action is front-loaded, and the quota note packs the API path and batching behavior into a single compact clause. Every element 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 write operation with four parameters and no output schema or annotations, the description covers the core action and quota but leaves gaps: no usage guidance versus siblings, no description of what the call returns, and no behavioral notes beyond chunking. Since the schema fully documents parameters, the tool is callable, but an agent lacks context for result handling and alternative selection.

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 with meaningful descriptions. The tool description adds no parameter-level semantics beyond what the schema provides; the quota note only hints at how playlist_id is consumed (GET playlist items). Baseline 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?

The description states a specific verb and resource: 'Save all tracks of a playlist to your Liked Songs (library)'. This clearly conveys the action and target, and implicitly distinguishes the tool from reverse-direction siblings like library_to_playlist and generic savers like save_to_library or save_items. However, it never names an alternative or explicitly differentiates, so it stops 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?

No guidance is given on when to choose this tool versus alternatives such as save_to_library, library_to_playlist, or add_to_playlist. There are no exclusions, prerequisites, or use-case conditions. The only extra sentence is about quota mechanics, which is implementation detail, not usage guidance.

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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