dataset_stats

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

With no annotations provided, the description must carry full behavioral disclosure. It implies a read-only operation ('show') but does not disclose error conditions, performance implications, or what happens when no dataset is in memory. Minimal behavioral detail beyond the obvious.

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 a single, concise sentence with no redundant words. It is front-loaded and every word contributes meaning, exemplifying strong conciseness.

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?

The tool is simple (0 params, output schema present), so the description need not explain return values. However, it lacks essential context about what 'in-memory dataset' refers to and how this tool relates to sibling tools like 'research_stats' or 'export_dataset', leaving a gap in overall completeness.

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 and an empty schema, so the description does not need to explain parameter semantics. The baseline of 4 applies, and there is no additional information required.

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 identifies the action ('Show') and the resource ('in-memory dataset statistics'), making the tool's purpose understandable. However, it does not distinguish it from sibling tools like 'research_stats' or 'export_dataset', and 'in-memory dataset' is somewhat ambiguous without parameter context.

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?

No guidance is provided on when to use this tool versus alternatives, nor any prerequisites such as requiring a dataset to be loaded. The description is purely declarative and offers no contextual usage direction.

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