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

Annotations already declare the safe read-only profile, but the description adds substantial behavioral context beyond them: a ~72h data delay, case-sensitive SKU identity rules, the source-coverage reporting caveat (do not infer continuous coverage from outer bounds), and the get_sales_summary fallback behavior. These are non-obvious traits an agent would otherwise get wrong.

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 and data source are front-loaded, and each sentence carries distinct information (metrics, delay, SKU rules, parent_asin, exclusions, coverage caveat, fallback). It is a dense single block that is slightly longer than necessary but avoids filler and repetition.

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 11 parameters with full schema coverage and an existing output schema, the description needn't explain return values, and it correctly focuses on the caveats that matter (coverage field, delay, fallback). An agent has everything needed to call it correctly and interpret gaps in the returned data.

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 schema already documents all 11 params (including case-sensitivity and parent_asin semantics). The description's parameter mentions (parent_asin for variation families, SKU case-sensitivity) largely restate what the schema and output already provide, adding only marginal elaboration. Baseline 3 is appropriate when 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+resource (historical total product performance from Business Reports) and enumerates the metrics returned (sales, sessions, page views, conversion, Buy Box, traffic split). It explicitly distinguishes itself from siblings like get_sales_summary, get_todays_sales, and ads performance tools, so an agent can route correctly without opening schemas.

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?

Gives explicit when-to-use (historical product performance, variation-family filtering via parent_asin) and when-not-to-use ('Do not use for current-day/yesterday account totals or ad-attributed campaign metrics') with named alternatives (get_sales_summary/get_todays_sales, ads tools). It also explains the fallback relationship so the agent understands overlap with get_sales_summary.

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