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raydollete

TIDAL Music MCP

by raydollete

recommend_tracks

Get music track recommendations based on your favorite tracks or specific track IDs, with options to filter by criteria like mood or genre.

Instructions

Recommends music tracks based on specified track IDs or can use the user's TIDAL favorites if no IDs are provided.

USE THIS TOOL WHENEVER A USER ASKS FOR:
- Music recommendations
- Track suggestions
- Music similar to their TIDAL favorites or specific tracks
- "What should I listen to?"
- Any request to recommend songs/tracks/music based on their TIDAL history or specific tracks

This function gets recommendations based on provided track IDs or retrieves the user's
favorite tracks as seeds if no IDs are specified.

When processing the results of this tool:
1. Analyze the seed tracks to understand the music taste or direction
2. Review the recommended tracks from TIDAL
3. IMPORTANT: Do NOT include any tracks from the seed tracks in your recommendations
4. Ensure there are NO DUPLICATES in your recommended tracks list
5. Select and rank the most appropriate tracks based on the seed tracks and filter criteria
6. Group recommendations by similar styles, artists, or moods with descriptive headings
7. For each recommended track, provide:
   - The track name, artist, album
   - Always include the track's URL to make it easy for users to listen to the track
   - A brief explanation of why this track might appeal to the user based on the seed tracks
   - If applicable, how this track matches their specific filter criteria
8. Format your response as a nicely presented list of recommendations with helpful context (remember to include the track's URL!)
9. Begin with a brief introduction explaining your selection strategy
10. Lastly, unless specified otherwise, you should recommend MINIMUM 20 tracks (or more if possible) to give the user a good variety to choose from.

[IMPORTANT NOTE] If you're not familiar with any artists or tracks mentioned, you should use internet search capabilities if available to provide more accurate information.

Args:
    track_ids: Optional list of TIDAL track IDs to use as seeds for recommendations.
              If not provided, will use the user's favorite tracks.
    filter_criteria: Specific preferences for filtering recommendations (e.g., "relaxing music,"
                     "recent releases," "upbeat," "jazz influences")
    limit_per_track: Maximum number of recommendations to get per track (NOTE: default: 20, unless specified otherwise, we'd like to keep the default large enough to have enough candidates to work with)
    limit_from_favorite: Maximum number of favorite tracks to use as seeds (NOTE: default: 20, unless specified otherwise, we'd like to keep the default large enough to have enough candidates to work with)

Returns:
    A dictionary containing both the seed tracks and recommended tracks

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
track_idsNo
filter_criteriaNo
limit_per_trackNo
limit_from_favoriteNo
Behavior4/5

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

No annotations are provided, so the description carries full burden. It discloses that recommendations are based on seed tracks, uses default limits, and instructs not to include seed tracks in results. However, it does not mention any side effects or authorization needs beyond the tool's purpose.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is excessively long (over 400 words) and includes extensive post-processing instructions for the AI (steps 1-10) that are not part of the tool's core definition. The essential purpose and parameters are buried among verbose guidance.

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?

Given the tool's complexity (seeds, filters, limits, and recommendation logic), the description is quite complete. It explains behavior when track_ids is empty, how limits work, and what the output contains. It could be improved by more explicitly stating the return format.

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 description coverage is 0%, but the description compensates by explaining each parameter in detail: track_ids (optional seeds), filter_criteria (string), limit_per_track (default 20, with rationale), and limit_from_favorite (default 20). It adds meaning beyond the schema's type and default values.

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 it recommends music tracks based on specified track IDs or the user's TIDAL favorites, and distinguishes from sibling tools by focusing on recommendations rather than search, playlists, or downloads.

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 explicitly lists when to use the tool with concrete examples (e.g., 'Music recommendations', 'What should I listen to?'). It does not explicitly state when not to use it, but the positive use cases are very 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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