Get product labels

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

Beyond the read-only/idempotent annotations, it discloses provenance ('the website's copy of each label', 'the packaging prevails'), an important interpretation caveat ('absence of an allergen... is not a "free from" claim', 'nothing is inferred'), a batch ceiling of 20, and that no login is needed. These are exactly the behavioural facts an agent needs before acting on allergen data.

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?

Front-loaded with what is returned, then usage, then caveats, with no filler sentences. It is dense and somewhat long, but every clause carries information the agent needs; the allergen caveat in particular earns its space.

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?

An output schema exists, so return values need no explanation, and the description covers the remaining gaps: batch limit, data provenance, interpretation limits on allergen absence, and auth requirement. Nothing needed to call and correctly interpret this tool 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 description coverage is 100% and the single parameter already documents productId syntax and slug acceptance. The description only reiterates the 'up to 20 products' ceiling that the schema's maxItems already enforces, so it adds little beyond the schema baseline.

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?

States a specific verb+resource (read the label of products) and enumerates the exact payload: ingredient list, capitalised allergen words, allergen and 'may contain traces' statements, and nutrients per 100 g/ml. An agent can distinguish this from get_product, which returns general product data, without opening either schema.

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?

'Use it only when a task needs them, such as checking vegan, gluten or allergens, or adding up protein' gives explicit positive triggers and an implicit exclusion (don't fetch labels gratuitously). It stops short of naming a concrete alternative sibling for when deeper product data is wanted, so it is clear context rather than full routing guidance.

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