deep_dive_report

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

No annotations are provided, so the description carries the full burden. It earns credit for disclosing the quota (GET /me/player/recently-played + 3x GET /me/top/artists), which conveys the cost and endpoint footprint, and for noting input flexibility. However, it never states that this is a read-only operation, nor does it address edge cases like an artist with no listening history or an invalid ID.

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 with zero waste: the core function is front-loaded, and the quota disclosure earns its place as operationally relevant context. Every word adds information.

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 core deliverable and API cost are covered, and response_format partially compensates for the absent output schema. But with no annotations and no output schema, the description should also confirm read-only behavior and cover failure modes; and given the dense sibling list, a usage-routing sentence would materially improve completeness.

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%, with clear per-parameter documentation for artist (ID/URI/URL), max_items (default and pagination), and response_format (enum meaning per value). The deescription's mention of accepted ID/URI/URL merely repeats the schema. Baseline 3 applies because the schema does the heavy lifting.

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?

States a specific verb ('deep-dive') with a resource ('one artist') and enumerates concrete outputs: recently-played counts, track rotation, and rank in each top-artists window. This is unambiguous about what the tool produces. However, it does not explicitly differentiate itself from the closely named sibling artist_deep_dive, so it loses the last point for sibling distinction.

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 implies a scenario (per-artist listening analysis) but offers no explicit when-to-use guidance, no exclusions, and no mention of alternatives. With a huge sibling set containing artist_velocity_report, track_rotation_report, and top_artist_ranking_delta, an agent is left to guess which composite analysis tool fits. The quota note gives operational context but not usage selection guidance.

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