Drop Beacon

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

Annotations already indicate this is a read-only, non-destructive, idempotent, and closed-world operation. The description adds useful context by specifying it checks 'currently in stock' status and returns retailer-specific data, which helps the agent understand the real-time nature and scope of results. However, it does not disclose additional behavioral traits like rate limits, authentication needs (beyond the optional API key in schema), or error handling, leaving some gaps.

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 in the first sentence, followed by return details and usage context in two additional sentences. Every sentence earns its place by adding value—no redundancy or waste. It is appropriately sized for the tool's complexity.

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, rich annotations (covering safety and idempotency), and 100% schema coverage, the description is mostly complete. It explains the tool's purpose, output, and usage context. However, without an output schema, it could benefit from more detail on return format (e.g., structure of per-retailer data), but the annotations help mitigate this 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?

Schema description coverage is 100%, so the schema already fully documents the two parameters (api_key and product). The description does not add any meaning beyond what the schema provides, such as explaining how the 'product' input is resolved or the impact of the optional API key. Baseline 3 is appropriate since the schema handles the parameter documentation adequately.

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 ('Check if... is currently in stock'), identifies the resource ('EDC product'), and distinguishes it from siblings by focusing on real-time availability rather than brand info, drops, trends, price comparisons, or general product searches. It explicitly mentions what it returns ('per-retailer availability, prices, and direct purchase links'), which further clarifies its unique 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 provides clear context for when to use this tool ('Useful for finding where to buy a specific product'), which implies it's for checking stock status of known products. However, it does not explicitly state when not to use it or name alternatives among the sibling tools, such as using 'search_products' for broader discovery or 'get_price_comparison' for price-focused queries without stock checks.

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