list_datasets

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

No annotations are provided, and the description adds minimal behavioral context beyond 'lists all datasets'. It does not disclose return format, authentication needs, rate limits, or scope (e.g., public vs. private). This is insufficient for a tool with no annotations.

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 concise with three short lines, front-loading the primary action and pagination. The total count is extraneous but not harmful. It earns its place, though a bit more structure (e.g., bullet points) could improve readability.

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?

For a simple paginated list tool with an output schema, the description is adequate but leaves ambiguity about the scope (e.g., all datasets across the user or system). Sibling tools provide some context, but the description itself could be more complete.

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 has 0% parameter descriptions, but the description explains 'offset and limit to page through results', adding meaning beyond the schema's defaults. This helps an agent understand the parameter purposes, though more detail could be added.

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 states the verb 'list' and resource 'datasets', distinguishing it from siblings like 'get_dataset' (single) and 'search_datasets' (filtered). It is specific and leaves no ambiguity about what the tool does.

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 explains pagination with offset and limit, but does not explicitly contrast with alternatives like 'search_datasets'. It implies usage for all datasets without querying, but lacks explicit when-to-use guidance.

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