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freddy24-7

spotify-mcp-server

by freddy24-7

search_and_add

Search for a track and add the top result to a Spotify playlist in one step.

Instructions

Search for a track and add the top result to a playlist in one step.

Parameters

query : str Free-text search query (e.g. "Shape of You Ed Sheeran"). playlist_id : str Spotify playlist ID or full URI to add the track to.

Returns

dict Keys: track_name, artists, track_uri, playlist_id.

Raises

ValueError If query is blank or the search returns no results. spotipy.SpotifyException Propagated if the Spotify API returns a non-2xx response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
playlist_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Since no annotations are provided, the description must disclose behavior. It explains the search-add flow, returns a dict with track details, and raises ValueError for blank/no-result queries and propagates SpotifyException. This covers key behavioral outcomes, though it omits potential side effects like playlist size limits or authentication requirements.

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 compact and structured with clear sections for parameters, returns, and raises. The opening sentence states the core action, and each subsequent line adds necessary detail without redundancy.

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

Completeness5/5

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

Given the tool's simplicity, the description covers purpose, all parameter semantics, return format, and errors. The presence of an output schema is noted, but the description's return documentation aligns with it, making the tool fully understandable.

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?

The schema only defines two string fields with no descriptions, while the description elaborates both: 'query' is a free-text search with an example, and 'playlist_id' accepts a Spotify ID or full URI. This fully 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 opens with a concise verb phrase 'Search for a track and add the top result to a playlist in one step,' which clearly identifies the tool's function and distinguishes it from sibling tools like add_to_playlist that likely require an existing track URI.

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 when to use this tool—when you have a free-text query and want to add the top match directly—but does not explicitly state alternatives or when not to use it. The one-step framing differentiates it from separate search and add operations, and the parameter examples provide contextual usage.

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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