get_sales_velocity

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

No annotations are provided, so the description carries the burden of explaining behavior. It conveys that this is a calculation over a trailing window of days, but it does not disclose output granularity, aggregation behavior, or how products with no sales are handled. The core action is clear, but behavioral detail is limited.

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 two short sentences, front-loaded with the core action and followed by a practical purpose. Every phrase earns its place and there is no redundancy or filler.

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 one-parameter calculation tool, the description covers the core calculation and the intended use. However, without an output schema, it leaves ambiguity about whether the returned average is per product or an aggregate across all products, and it does not explicitly differentiate use cases from get_current_stock.

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%, and the schema already documents 'days' with examples (7, 15, 30). The description only restates the concept of 'últimos X días' without adding semantic detail beyond the schema, so the baseline score of 3 applies.

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 computation ('Calcula el promedio de ventas diarias de los productos') and pairs it with a clear use case ('predecir cuándo se agotará el stock'). This distinguishes it from siblings like get_current_stock, which concerns current inventory levels, and create_ai_recommendation, which generates recommendations.

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 gives a clear context for when to use the tool: when forecasting stock depletion based on recent sales velocity. It does not explicitly name sibling tools or provide exclusion criteria, but the practical use case is sufficient guidance for this simple tool.

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