Rating Distribution

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

With no annotations provided, the description carries the behavioral burden. It discloses the two main behaviors: producing a histogram and computing a pooled share across all ratings in scope. It also clarifies that the histogram uses per-book mean ratings, which is a useful aggregation detail. It does not mention side effects or permissions, but as a read-only analytics tool this is not a major gap.

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 three concise sentences with no filler. The output definition is front-loaded, followed by illustrative questions. Every sentence earns its place.

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?

Given the full input schema, complete parameter descriptions, and an output schema, the description is largely complete for correct invocation. It explains the core output metrics well enough to interpret results. The only missing piece is explicit guidance about when a sibling tool would be a better choice.

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%, so the baseline is 3 even though the description itself does not explain parameters. The description reinforces the meaning of bucket_size by mentioning per-book mean ratings and 'in scope' filters, but it does not add substantial parameter-level detail beyond the schema.

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 what the tool computes: a histogram of per-book mean ratings plus a pooled share of 1-5 star ratings. This is specific to the rating_distribution resource and distinguishes it from sibling tools focused on top-rated books, language stats, or user-vs-book comparisons. The example questions further make the purpose concrete.

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 to use the tool by framing the questions it answers, such as 'are ratings clustered high?' and 'what does a typical rating look like?'. It does not explicitly name sibling alternatives or state when not to use it, so it stops short of full exclusion guidance.

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