skip_stats

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

Beyond the readOnlyHint annotation, the description discloses the exact derivation logic (reason_end='fwdbtn' AND played under the skip threshold), that the derived rate can disagree with the raw 'skipped' field, and that min_plays filters low-sampple noise. It does not describe the output columns or ordering, but the core behavioral traits are transparent.

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 compact and front-loaded. It names the tool's output, explains the key metric formula and caveat, and points to a related tool, all without fluff or redundancy.

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 statistics tool with no output schema, the description explains the grouping options, the metrics reported, and the min_plays threshold purpose. The only meaningful omission is limit's behavior and the exact response shape, but enough context is provided for an agent to invoke the tool correctly with defaults.

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?

The schema provides only defaults and titles, so the description must carry parameter meaning. It does add meaning for group_by ('artist, track, or month') and min_plays ('filters out low-sample noise'), but limit is not described at all. This leaves a clear gap for a parameter that controls leaderboard size.

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: 'Skip-rate leaderboard grouped by artist, track, or month.' This fully captures what the tool computes and clearly differentiates it from sibling stats tools like listening_summary or listening_by_hour.

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 gives clear context for when this tool is relevant (skip-rate analysis) and mentions describe_listening_data as a reference for the skip definitions. It does not explicitly say when not to use it vs. siblings, so it stops short of a 5.

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