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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description goes beyond annotations by disclosing behavioral traits: it returns 'best match first', it prefers priced and recently observed rows, it returns specific fields (ASIN, brand, title, price, rating, image), and it restricts one barcode per call. It doesn't describe edge cases like no-match behavior, but the disclosure of ranking logic is valuable.

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, all information-dense: purpose, formats, usage conditions, return behavior, ranking, fields, and constraint. The most important information is front-loaded ('Look up products by retail barcode'), and no sentence is wasted.

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 read-only lookup with two fully documented parameters and no output schema, this description is complete enough for an agent to select and invoke the tool correctly. It covers input formats, use cases, return fields, ranking, and the one-barcode constraint. No critical operational guidance is missing.

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%, so the input schema already explains both parameters in detail. The description reinforces that the barcode is numeric and gives accepted formats, which slightly adds context, but it doesn't add meaning beyond the schema for marketplace_id. Baseline 3 is appropriate because the description adds minor value but the schema carries 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?

The description states a specific verb ('look up'), a precise resource ('products by retail barcode'), and enumerates the barcode formats (UPC-12, EAN-13, GTIN-14). It also gives concrete example queries and distinguishes the tool's function by clarifying it maps barcodes to Amazon or Walmart listings. Siblings like search_products and find_product_across_web are distinct enough in name, but this description also explicitly explains the barcode-to-listing purpose.

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 description explicitly states when to use the tool: when the user supplies a numeric retail barcode from a shelf tag, invoice, supplier price list, or wholesale catalog and wants to know the Amazon/Walmart listing. It also provides example user phrasings and notes 'One barcode per call', an implicit boundary. It does not name a specific sibling alternative, but the use-case conditions are clear enough that an agent can decide without comparing schemas.

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