Drop Beacon

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

Annotations already provide strong behavioral hints (read-only, non-destructive, idempotent, closed-world), so the bar is lower. The description adds useful context about the specific data returned (e.g., price range, top 5 products) and the tool's purpose for research/comparison, but does not disclose additional behavioral traits like rate limits, authentication needs beyond the optional API key in the schema, or error handling.

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 description is front-loaded with the core purpose and detailed return data, followed by a concise usage context. Both sentences earn their place by providing essential information without redundancy or fluff, making it highly efficient and well-structured.

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?

Given the tool's moderate complexity (brand info retrieval), rich annotations (covering safety and idempotency), and no output schema, the description is mostly complete. It details the returned data and usage context, but could improve by mentioning potential limitations (e.g., brand not found) or output format specifics to fully compensate for the lack of output schema.

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%, with clear documentation for both parameters (brand name/slug and optional API key). The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining format requirements or usage examples for the 'brand' parameter. Baseline score of 3 is appropriate when the schema fully covers parameters.

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 clearly states the specific action ('Get detailed information') and resource ('an EDC brand'), and enumerates the exact data returned (product counts, price range, categories, top products). It distinguishes this tool from siblings by focusing on comprehensive brand-level data rather than availability checks, drops, trends, price comparisons, or product searches.

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 provides clear context for usage ('Useful for brand research and comparison'), which implicitly suggests when to use this tool. However, it does not explicitly state when not to use it or name specific alternatives among the sibling tools, such as using 'search_products' for individual product queries instead.

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