Stats By Publisher

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

With no annotations, the description carries full weight and it does so well by exposing the key behavioral trap: publisher is free text, each row is one spelling, 79,423 distinct values exist, and Penguin alone spans multiple rows. This prevents agents from misinterpreting aggregate figures as publisher-level totals.

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 purpose is front-loaded in the opening sentence, and the caveat is delivered in a compact, single backticked paragraph with a concrete example. Every sentence adds value and there is no boilerplate 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 an 8-paramater tool with a fully described schema and an output schema, the description covers the main conceptual hazard and how to read the numbers. It narrowly misses full completeness because it never explicitly routes the agent toward or away from sibling stats tools, but the tool name and purpose phrase make that gap minor.

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% and each parameter already has a rich description, including the same unnormalised-publisher warning in min_books. The description adds texture with cardinality counts and the Penguin example but does not introduce new parameter semantics beyond what the schema already provides, so the baseline 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 statement of what the tool returns: rating statistics grouped by publisher string. The phrase 'publisher string' rather than 'publisher' immediately distinguishes this from stats_by_author, stats_by_language, and stats_by_year, and the warning about unnormalised spelling sets precise expectations.

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?

It gives implied usage guidance: use this for publisher-level stats, and treat results as per-spelling lower bounds. However, it does not explicitly name alternative tools or state when not to use this tool, leaving the actual selection to inference from the purpose clause.

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