product_details

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

With no annotations, the description carries the behavioral burden. It discloses several outputs (last bought, last used, shelf life, spoil rate, open amount, minimum stock) and implies a read-only lookup. However, it does not state the absence of side effects explicitly, nor does it describe error behavior, authorization needs, or what happens if the product is not found.

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 relatively compact and front-loads the core behavior ('Everything Grocy knows about one product') before listing output fields and the parameter format. Every sentence adds content, though the field list is somewhat long and could be tightened.

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?

The description covers what data is returned, the intended decision context, and the flexible input format, which is adequate for a simple one-parameter lookup. However, with no annotations, no output schema, and no sibling or error guidance, an agent is left without signal about failure modes or how this relates to tools like stock_history or search_products.

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 0%, and the schema only says the parameter is a string. The description's 'Args' section adds valuable meaning by explaining that 'product' can be a product name, description fragment, or barcode. However, because this is the only piece of parameter documentation and output details are bundled into the description rather than schema, the parameter semantics coverage remains thin.

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 identifies the resource ('one product') and scope ('stock, dates, and history'), and enumerates the specific data returned. However, it lacks an explicit verb like 'retrieve' or 'get', and it does not explicitly distinguish itself from sibling tools such as stock_history or search_products.

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 a clear use context: deciding whether to restock a product or stop buying it ('the context for deciding whether to restock something or stop buying it'). It does not mention exclusions or when to prefer sibling tools, but the single-product context is reasonably clear.

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