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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds real behavioral context beyond that: result ordering (biggest drop first), the 7-day window, INR currency, and the sign convention for priceChange ("negative"). It does not address result volume, pagination, or empty-result behavior, which are the remaining unknowns for an agent deciding whether one call suffices.

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 the core definition, then usage examples, then parameter guidance, then the output shape. Every sentence carries distinct information: scope, ordering, trigger phrases, brand/keyword mechanics, priceChange semantics, and rendering. No filler or repetition.

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?

For a four-parameter read tool with an output schema and full annotation coverage, nothing essential is missing. It even explains the one non-obvious return field (priceChange as a negative INR delta) and how results surface to the user as product cards, despite the output schema making that optional.

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 100%, so the schema already documents all four parameters including defaults, bounds, and examples; baseline 3 applies. The description does add marginal meaning — pass the brand verbatim as the user wrote it, and keyword narrows to a product type with examples — but most of this overlaps the schema's own examples and 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?

States a specific resource with scope and ordering: "A brand's products whose prices dropped recently (up to the last 7 days) across Indian online stores, biggest drop first." That is enough to distinguish it from a generic product search, but it never names the sibling top_price_drops or explains how it differs, so an agent must infer the brand-scoped vs. cross-brand split.

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?

Gives concrete trigger phrases ("Samsung price drops", "what Philips products got cheaper", "any deals on boAt this week") and shows the brand+keyword combination pattern, which is clear when-to-use guidance. It stops short of explicit exclusions or naming an alternative tool for the cross-brand case, so it lands at 4 rather than 5.

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