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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), but the description adds substantial value beyond them: the credit cost model (1 credit, +0.5 with history, 0 for unknown id), which operations are free, the 11-marketplace scope, and the paid-plan requirement. This is exactly the kind of behavioral context annotations can't express.

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?

Long but dense and front-loaded: what it returns, then USE WHEN, then input modes, then cost. Nearly every clause carries information, though the enumeration of return fields is on the verbose side and could be tightened.

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?

There is no output schema, so the description must carry return semantics - and it does, listing the full set of profile fields, the sub-category/brand behavior for root vs non-root categories, and what history=true appends. Nothing an agent needs to call this correctly is missing.

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 per-parameter docs are already present, but the description adds cross-parameter semantics the schema alone doesn't convey: the OR relationship between category_id/node_id, q, and list=true, and that q returns candidates first (free) so the caller can pick an id. That mutual-exclusivity and sequencing is genuine added meaning.

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 ('Amazon CATEGORY landscape') and enumerates exactly what the profile contains: size, pricing/rating averages, Amazon retail share, FBA penetration, private-label share, HHI concentration, churn, demand signals, benchmarks, sub-categories and top brands. An agent can immediately tell this is a category-level analytics tool, distinct from product/brand/seller siblings.

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?

Explicit 'USE WHEN' clause names the triggers (how competitive / Amazon-dominated / FBA-heavy, how big, which brands lead, sizing a private-label or wholesale entry). It also documents the three invocation modes and when to choose each, plus the free vs paid conditions.

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