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

Annotations only cover the safety profile (readOnly, idempotent, non-destructive), and the description adds substantial behavioral detail beyond them: the 7-day price-history verification rule, exclusion of prices raised before a sale, ordering by largest drop, a no-commission ordering guarantee, and the seller-diversity behavior of max_per_seller. This is rich methodology disclosure an agent cannot get from structured fields.

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 purpose is front-loaded and each sentence adds distinct information (methodology, filters, ordering). It runs long and dense, but virtually no sentence is wasted, so it stays efficient for the amount of behavior it must convey.

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?

An output schema exists, so return-value shape need not be described, and annotations cover safety. The description completes the verification semantics and filter behavior well; the only omission is any note on the limit parameter, which is a small residual gap.

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 0% schema description coverage, the description must carry parameter meaning, and it does for three of four: min_percent_off range (1-90), query filters by title/seller words, and max_per_seller's default of 3 and its purpose. Only limit is left unexplained, a minor gap given its self-evident 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?

The description states a specific verb+resource: it lists products from independent Shopify sellers whose price Shoptegrity recorded as genuinely dropped. It sharply differentiates from siblings (e.g. check_deal/browse_alternatives) by framing the result set as verified drops rather than 'headline discounts,' so an agent knows exactly what this returns.

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 clear context for when this applies — verified drops for Black Friday/Cyber Monday, real drops vs. headline discounts — which implies the appropriate shopping-research scenario. It does not, however, explicitly name which sibling to use instead for related needs (e.g. check_deal for a single item), so routing is left to inference.

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