list_skus

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

No annotations are provided, so the description must carry more weight. It states that it lists 'every' ID in the dataset, but is otherwise silent on behavioral aspects like whether it returns duplicates, how the dataset is loaded or refreshed, or what happens if the dataset is empty. Given the tool's simplicity and zero parameters, the description is adequate but lacks nuance.

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?

Single sentence, 7 words, front-loaded with the action and object. Every part is informative and there is no redundancy. Highly concise.

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 that there are no parameters, the output schema exists (so return values are documented), no nested objects, and the tool's purpose is straightforward, the description is entirely sufficient. An agent can determine when to call this tool (to discover available IDs) with complete confidence.

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?

The schema has no parameters and schema description coverage is 100%, so there is nothing for the description to add about parameter meaning. The baseline for zero-parameter tools is high, and the description does not need to elaborate, earning a 4.

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 uses a specific verb ('list') and resource ('SKU/series id'), and the scope is clearly defined ('in the loaded dataset'). It distinguishes itself well from sibling tools like 'classify_demand_pattern' or 'forecast_series', which are analytical or predictive rather than listing identifiers.

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 implies that use of this tool is appropriate before performing tasks that require specific SKU/series IDs. However, there is no explicit guidance on when not to use it or how it relates to siblings—for example, whether listings from other tools differ. Still, the context is clear enough for an agent to decide, especially given it has no parameters.

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