library_genre_report

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

No annotations are provided, so the description carries the full behavioral burden. It discloses meaningful traits: a full-library scan (cost implication), a join against the user's tag sidecar (external dependency), and a coverage limitation ('only artists you have tagged appear here'). It does not mention read-only safety, pagination, or performance explicitly, but for a read-style report tool the disclosed traits are substantive.

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?

Three sentences with zero waste: purpose first, mechanism second, limitation/why third. Each sentence earns its place and the most decision-relevant fact (user-declared tags, not Spotify genres) is front-loaded.

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?

For a two-parameter aggregation tool with fully documented schema and no output schema, the description covers purpose, data dependency, report contents (per-genre counts plus artists), and coverage boundaries. Minor gaps remain: no guidance on what happens with zero tags, no explicit note that the full-library scan may be slow, and no pointer to sibling genre tools for contrast.

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% — both max_results and response_format already carry their own descriptions, including defaults, enum values, and semantics. The tool description adds no parameter-specific detail beyond what the schema provides, so the baseline of 3 applies.

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 opens with a specific verb and resource ('Aggregate your saved library by user-declared genre tags') and then details the mechanism: scanning saved tracks/albums, joining against the tag sidecar, and reporting per-genre counts plus contributing artists. It also differentiates itself from genre tools that use Spotify's own genre metadata ('Genres are unavailable from Spotify itself'), which helps distinguish it from siblings like top_genre_census and genre_trends_over_time.

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 when this tool applies: it is the right choice when genre aggregation depends on user-declared tags rather than Spotify's genre data, and it references tag_management as the data dependency. However, it never explicitly names alternatives or states when NOT to use it (e.g., when the user wants Spotify-sourced genre stats), so exclusions are left to inference.

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