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

Annotations already mark the tool as read-only and non-destructive, so the description does not need to state safety. It adds valuable behavioral context by explaining that the tool returns matching ASINs with current scores, product identity, fulfillment split, and explicitly frames the output for user confirmation rather than immediate mutation.

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?

Three sentences, each earning its place: the first states the function, the second gives concrete usage triggers, and the third captures the output dimensions. It is front-loaded and avoids filler.

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?

The tool is complex (19 optional parameters, no output schema), and the description covers the core intent and return value but not the parameter space or how filters combine. No output schema means the description is the only source of return-structure guidance, and it stays at a high level, leaving an agent guessing about ordering, shape, or behavior when both asin and brand are supplied.

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?

With schema description coverage at only 26% and 14 undocumented parameters, the description needed to compensate, but it does not. It broadly references brand, scores, and fulfillment, which maps to a few fields, but says nothing about the many threshold/contains/percentage filters such as min/max_price, min/max_composite_score, asin_contains, product_title_contains, or observed buybox day ranges.

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 opens with a specific verb and resource: 'Resolve a natural-language watchlist request into concrete ASINs the user can add.' This positions it as a resolution/confirmation tool rather than a direct mutation, distinguishing it from sibling watchlist_add without needing to open schemas. The example phrases reinforce the exact intent it serves.

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?

It gives explicit triggering scenarios with concrete natural-language examples and broadens to 'any watchlist-creation intent.' It does not spell out when not to use it or name watchlist_add as the direct-add alternative, but the context is clear enough for an agent to select it for free-form watchlist requests.

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