list_curated

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

No annotations are provided, but the description discloses that the output is a sorted list of dataset IDs and characterizes the data (curated, with specific filter behavior). This is adequate for a simple read-only tool, though it lacks details on caching or live-fetching.

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 only four sentences, each serving a purpose: stating the action, explaining the concept, pointing to related tool, and declaring the output format. No redundant or vague language.

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 simplicity (no parameters, clear output), the description covers its role and relationship to siblings. It could mention error cases or performance notes, but for a list command this level is sufficient.

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 tool has zero parameters, so the input schema coverage is 100%. Per guidelines, baseline 4 applies, and the description adds no parameter information as none is needed.

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 explicitly states the action (List) and the resource (every curated dataset ID), and distinguishes from siblings by explaining the meaning of 'curated'—datasets accepting plain-English filters—which sets it apart from describe_dataset and get_data.

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 hints at when to use this tool (to find curated datasets) and directs users to describe_dataset for documentation, but does not explicitly state when not to use it or compare directly to search_datasets.

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