get_recommendations

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It states the tool 'Get track recommendations' but lacks details on permissions, rate limits, response format, or how recommendations are generated (e.g., algorithm, personalization). For a tool with no annotation coverage, this leaves significant gaps in understanding its operational behavior.

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?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part ('Get track recommendations based on seed tracks, artists, or genres') directly contributes to understanding the tool's function, making it appropriately sized and well-structured.

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?

Given no annotations and no output schema, the description is incomplete for a tool with 4 parameters and behavioral complexity. It covers the basic purpose but lacks details on usage context, behavioral traits (e.g., response format, error handling), and output expectations, which are critical for an AI agent to invoke it correctly without structured guidance.

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 description coverage is 100%, providing clear documentation for all parameters (seed_tracks, seed_artists, seed_genres, limit). The description adds minimal value by mentioning these parameters in context ('based on seed tracks, artists, or genres') but doesn't explain semantics beyond what the schema already covers, such as how seeds are weighted or combined.

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 verb 'Get' and resource 'track recommendations', specifying the purpose as generating recommendations based on seed inputs. It distinguishes from siblings like 'search' or 'get_available_genres' by focusing on personalized recommendations rather than direct retrieval or genre listing. However, it doesn't explicitly differentiate from all siblings (e.g., 'get_artist_related_artists' also provides recommendations but for artists).

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing seed inputs), exclusions (e.g., not for general search), or comparisons to siblings like 'search' (for broad queries) or 'get_artist_related_artists' (for artist-specific recommendations). Usage is implied through the mention of seed parameters but not explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.