dashai_list_datasets

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

Annotations already provide readOnlyHint, idempotentHint, and destructiveHint, so the description doesn't need to restate these. It adds value by detailing the exact return fields (id, name, date, status) and the empty response behavior, which are not evident from annotations alone.

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 well-structured with a clear summary, sections for args and returns, and a bullet-point parameter explanation. Every sentence adds value and there is no redundant fluff.

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 (one optional parameter), the description covers the purpose, usage, return format, and empty-case behavior. It also references a sibling tool for deeper inspection, making the description fully self-contained for an agent to invoke correctly.

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 description explains the 'limit' parameter with its range (1-200) and default (50), which compensates for the low schema description coverage (0% as per context). It provides enough detail for an agent to use the parameter correctly without relying solely on the schema.

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 ('Lists') and a clear resource ('datasets loaded in dashAI'). It clearly distinguishes from sibling tools like dashai_describe_dataset by specifying it returns only summary fields, making it easy for an agent to choose this tool for overview purposes.

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 explicitly states when to use this tool ('just enough to pick one') and directs the user to dashai_describe_dataset for detailed column information. It also explains the behavior when no datasets exist, giving clear context for expected use cases.

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