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

Annotations already establish read-only, idempotent, non-destructive behavior, so the safety profile is covered. The description adds genuine domain context beyond them: what the payload contains (generation chain, size_variants with per-model caveats, buy_links) and two interpretation rules ('Missing size data is unknown', 'Do not apply generation-level battery ranges to individual sizes').

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-loads the search behavior, then lists the returned fields, then the two caveats. Dense but each clause earns its place; the caveat sentences are the most valuable part and are not padding.

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-structure explanation is not strictly required, yet the description still flags the analytical pitfalls (unknown sizes, generation-vs-size battery ranges) an agent would otherwise get wrong. Only the missing sibling routing keeps it from being fully complete.

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% and the sole parameter is documented as 'Full or partial product name'. The description reinforces partial-match semantics and supplies examples, adding modest value beyond the schema.

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 and resource ('Find products by (partial) name') and grounds it with concrete examples ('fenix 9', 'forerunner 970'). It implies a different scope than siblings like get_releases or compare_generations, but never names them, so differentiation is left to inference.

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?

The partial-name matching semantics imply when this tool is appropriate, and the interpretation caveats help after the call. But there is no explicit when-to-use/when-not guidance and no routing against compare_generations, get_releases, or get_predictions.

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