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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=true), so the bar is lower. The description adds real behavioral context beyond them: the call aggregates several analyses at once and 'Shows as a visual report in apps that support it,' which tells an agent the output may be rendered rather than returned as plain data. It stops short of disclosing cost/credit consumption or latency, which would matter for a multi-analysis aggregate.

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?

Two sentences, no filler, and the contents of the teardown are front-loaded before the routing guidance. Every clause carries information the agent needs (what it returns, how it renders, when to choose it).

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 convey return content — and it enumerates the delivered analyses precisely, plus notes the visual-report rendering. Combined with 100% parameter coverage and read-only annotations, an agent has everything needed to call it correctly.

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% with only three parameters, each already documented including the marketplace enum list and the keyword default. The description only echoes the keyword ranking concept already stated in the schema, adding no new syntax, format, or constraint detail. Baseline 3 applies 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?

Specific verb+resource ('Full teardown of one Amazon product in a single call') followed by an explicit enumeration of the composite outputs: complaint themes, 90-day rank/price/review history, 0–100 listing audit, keyword ranking, advertisers, and takeaways. This clearly separates it from the granular siblings like amazon_review_complaints or amazon_listing_audit.

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?

Explicitly states when to prefer it: 'Prefer this over calling the individual tools when the user wants an overview of a competitor.' It names the alternative class (the individual tools) and the condition (overview intent) that selects this one, so no inference is required.

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