describe_dataset

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

Annotations already declare readOnlyHint=true, so the safety profile is covered. The description adds useful behavioral context about auto-pagination on wide tables (60+ columns) and the performance benefit of a single call. It does not contradict annotations and provides meaningful additional detail about how the tool behaves.

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 tightly written with four sentences, each earning its place. It opens with a strong front-loaded label ('Primary orientation tool'), then explains outputs, value proposition, and edge-case handling. There is no fluff or repetition.

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 (3 params, no output schema), and the description covers all key aspects: what it returns (column metadata), why to use it (orientation), and how to handle wide tables. The return content is explicitly enumerated, so no essential information is missing.

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 description coverage is 100%, so the baseline is 3. The description adds value beyond the schema by explicitly explaining the purpose of columns=[] and columns_offset in the context of pagination, which is not fully captured in the schema descriptions. This lifts the score above the baseline.

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 tool's function: 'Returns every column's name, type, cardinality, null%, and sample values.' It also positions itself as the 'Primary orientation tool,' which distinguishes it from sibling tools like describe_column and get_distribution. The verb+resource structure is specific and unambiguous.

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 provides clear guidance on when to use the tool: 'Primary orientation tool' and 'A single call replaces reading the entire source file.' It also gives actionable instructions for wide tables (use columns=[] or columns_offset). However, it does not explicitly name alternative tools or state when NOT to use this tool, which prevents a 5.

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