library_growth_report

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

With no annotations provided, the description carries the full burden, and it does disclose the key behavioral trait 'Read-only' as well as the bucketing-by-added_at behavior. It does not, however, describe what the report output contains (counts, deltas, growth percentages) or any volume/cost caveats, leaving the result semantics to the agent's inference.

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?

A single front-loaded sentence states the core question, the aggregation method, the covered content types, the periods, and the read-only guarantee. Every phrase earns its place, with no repetition of schema contents.

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 low-complexity tool with three optional, fully documented parameters, the description plus schema is nearly sufficient to invoke the tool correctly. The gaps are the lack of differentiation from the similarly named `library_growth_timeline` sibling and the absence of any description of the return content (and there is no output schema to fill that void), so an agent could plausibly mis-select or misunderstand the result.

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 coverage is 100% — all three parameters (period, lookback, response_format) have explicit descriptions, defaults, and enums, so the schema does the heavy lifting. The description adds marginal value by tying the period values to the added_at bucketing basis and enumerating the content types counted, which is slightly beyond the schema but does not compensate for anything missing.

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 names a specific resource ('saved tracks/albums/shows/episodes'), an aggregation basis ('added_at period'), and the grouping granularity ('weekly/monthly/yearly'), so an agent can tell what this tool computes. However, it does not distinguish itself from the sibling `library_growth_timeline`, which plausibly covers nearly the same question, so it falls short of full differentiation.

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 opening phrase 'How fast your library is growing' implies the tool is for growth-rate questions, giving an agent a reasonable cue for when to invoke it. But no explicit when-to-use/when-not-to-use guidance is provided, and no alternative tools (e.g., `library_growth_timeline`, `saved_library_delta`) are named for comparison.

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