Deep Match: technical match by rhythm, timbre and key — great for building DJ sets. Requires a Pro or Studio plan.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, and destructiveHint as false. The description adds value by specifying the matching criteria (rhythm, timbre, key) and the plan requirement, which are behavioral constraints not captured in annotations. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. The purpose is front-loaded, and the plan requirement is clearly stated. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema and annotations, the description omits critical information about the single required input parameter ('url'). This is a significant gap that makes the tool description incomplete, as the agent cannot determine what to provide.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no description for the 'url' parameter in the schema). The description does not explain what the 'url' parameter should contain (e.g., track URL, playlist URL). With 0% coverage, the description must compensate, but it fails to provide any parameter guidance, leaving the agent to guess.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'technical match by rhythm, timbre and key' and specifies its use case 'great for building DJ sets.' This distinguishes it from siblings like 'find_similar' which may be more general, and 'playlist_match' which likely focuses on playlist-level matching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context: 'great for building DJ sets' and the plan requirement 'Requires a Pro or Studio plan.' However, it does not explicitly contrast with siblings or state when not to use this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have distinct purposes: deep_match for technical DJ matching, find_similar for general sonic similarity, generate_playlist for creating full sets, inspire_me for personalized discovery, playlist_match for multi-track centroid matching, and surprise_me for broad discovery. However, inspire_me and surprise_me both relate to discovery with overlap in scope, causing minor ambiguity.
Tool names use a mix of verbs and descriptive phrases (deep_match, find_similar, generate_playlist, inspire_me, playlist_match, surprise_me). The pattern is not fully consistent; some use verb_noun (generate_playlist) while others use verb_adjective (find_similar) or are more abstract (inspire_me). Not chaotic but lacks a uniform structure.
6 tools is well-scoped for a music discovery server. Each tool covers a specific function without redundancy, covering technical matching, similarity search, playlist generation, personalized discovery, group matching, and broad exploration. The number feels balanced and appropriate.
The tools cover core music discovery workflows: single-track matching, multi-track centroid matching, playlist generation with energy flow, and personalized/random discovery. Minor gaps include lack of explicit CRUD for user playlists beyond generation and no tools for browsing or managing user history directly.
