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

With no annotations, the description carries the full behavioral burden. It discloses the ordering behavior ('in the order given') but does not mention case sensitivity, exact matching, return format (full rows vs. just the column), or behavior with zero matches. This is minimal but non-trivial.

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, front-loaded sentence with no fluff. It conveys the core action and the key behavioral nuance (ordering) efficiently.

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 no output schema and no annotations, the description is somewhat sparse. It does not state the return format (all columns or only the matched column), potential edge cases (e.g., empty result), or prerequisites (e.g., valid column name). For a simple fetch tool it is adequate but not fully 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 description coverage is 0%, so the description must explain parameters. It does state the relationship between 'column' and 'values' ('whose column is any of the given values') and adds the ordering nuance. However, it does not clarify types, minItems/maxItems constraints, or that values are an array beyond what the schema implies. It partially compensates.

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 ('returns rows'), names the resource ('Enpso dataset'), and precisely defines the selection criterion ('whose column is any of the given values') along with ordering ('in the order given'). This clearly distinguishes it from siblings like dataset_row (single row) and dataset_search (general search).

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 phrase 'for "X vs Y" questions' gives a clear usage context for comparing specific values. However, it does not explicitly mention when not to use it or name alternative tools, so it stops short of full guidance.

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