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

Annotations are empty, so the description carries the full load - and it does meaningfully: read-only SELECT constraint, mandatory WHERE date BETWEEN window for product_performance_view, a 1000-row return cap, report_date/report_granularity requirement for best-seller views, and an instruction to cite account and date range. It does not cover auth/permission behavior beyond the account parameter, keeping it short of 5.

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?

Front-loaded with purpose and constraint, then tables, then a concrete example, then return limits and citation rules - a logical order. It is long, but nearly every clause (columns, enum marketing_method, required date filter, row cap) 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?

With no output schema and no annotations, the description still supplies the return shape (at most 1000 rows, columns determined by the SELECT), pagination via next_page, and the required date-scoping. The main residual gap is that authorization/scope behavior for multi-account reads is only hinted at via the account parameter.

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%, so baseline is 3, but the description goes well beyond the schema's terse 'A Merchant Reports SELECT query' by documenting the query dialect, table schemas, required WHERE clauses, and an example SELECT. The 1000-row cap also implicitly explains the next_page token, which the schema only labels generically.

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 (run Merchant Center reports) against a specific resource (a SQL-like Merchant Reports query), and clarifies it is SELECT-only. It does not explicitly differentiate itself from merchant_product/merchant_products/merchant_status, but the reporting-versus-product-management split is inferable from the table names.

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 tells the agent what the query language is and which tables exist, which implies when the tool is appropriate (analytics over products, prices, best sellers). It never states when not to use it or which sibling (merchant_product, merchant_products, merchant_status) to prefer for lookups, so usage selection is only implied.

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