create_vibe_playlist

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

With no annotations, the description carries the full burden. It discloses the main multi-step behavior (creates playlist, resolves queries, adds tracks) and imposes a constraint on song_queries. However, it does not cover failure handling, behavior on unmatched queries, or side effects on existing playlists.

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 concise and front-loaded, with the core action in the first sentence. There is minor redundancy between 'searching and adding matched songs' and the later 'resolves each query to a Spotify track, and adds them,' but each sentence adds useful clarity.

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?

The output schema covers return values, so the description focuses on behavior. It explains the full workflow and the LLM's responsibility for song_queries, but doesn't mention edge cases like missing query results or explicitly position this tool as a combined alternative to create_playlist and add_songs_to_playlist.

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 0%, but the description compensates by clarifying the role of song_queries (search queries resolved to tracks) and vibe (the prompt). It doesn't detail 'market', 'public', or 'description', but those are standard for playlist creation and the core parameters are explained.

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 a specific verb and resource: 'Create a playlist from a vibe prompt by searching and adding matched songs.' It distinguishes itself from sibling tools like create_playlist (which likely creates an empty playlist) and add_songs_to_playlist by describing the combined search-and-add behavior.

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 clear context for use: the LLM should supply song_queries that fit the vibe, and the tool handles the rest. It doesn't explicitly list alternatives or exclusion cases, but the implied workflow is understandable.

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