brand_buybox_trajectory

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

Annotations already declare readOnlyHint: true. The description adds that it returns weekly data for a trailing window, but does not disclose limits (e.g., max 52 weeks from schema), behavior for insufficient data, or how filtering parameters affect results. It does not contradict annotations.

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 extremely concise: two sentences with key purpose and output, followed by example queries. Every sentence adds value, and the most critical information is front-loaded.

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?

Despite good annotations, the tool has 16 parameters and no output schema. The description provides minimal behavioral context (trailing window, weekly seller counts) but omits explanation of filtering parameters (e.g., trend_in, min_seller_count_change_pct) and the structure of the return data. This leaves agents underinformed for correctly invoking the tool or interpreting results.

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 only 38% (most parameters lack descriptions). The description adds no parameter-specific information beyond what the schema provides, failing to compensate for the low coverage. Only 'brand', 'since_weeks', and 'marketplace_id' are somewhat explained in the schema; the many filter parameters are opaque.

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 the tool shows buybox concentration change over time, specifies the output (weekly seller counts and observed buybox days), and provides example queries that distinguish it from siblings like brand_under_attack or find_deconcentrating_brands.

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 explicitly lists use cases and example queries ('is this brand getting more competitive', 'concentration trend for Nike'), guiding when to invoke. It does not explicitly state when not to use or offer alternatives, but the context is clear enough for most scenarios.

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