inspect_Column

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

With no annotations, the description must disclose behavioral traits. It only states the basic action of giving a summary, without mentioning error cases, side effects, or what the output format will be. This leaves the agent without enough information about what to expect.

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, simple sentence with no wasted words. It is efficiently written, though it sacrifices completeness for brevity.

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 tool with two parameters and no annotations, the description is too minimal. It doesn't explain what the detailed summary contains (e.g., data type, missing values) or what the output schema provides, making it incomplete for reliable tool selection.

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 schema has two parameters (path, col_name) with 0% description coverage. The description vaguely references 'specific column/feature' but does not explicitly explain that path is the dataset location and col_name is the column to inspect, which is insufficient for a low-coverage 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 clearly states the tool's action ('Gives a detailed summary') and resource ('specific column/feature'), distinguishing it from sibling tools like get_dataset_overview and dataset_shape which operate at the dataset level. However, it lacks specificity about what the summary includes, leaving some ambiguity.

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 no guidance on when to use this tool versus alternatives, such as get_dataset_overview or analyze_target. It does not mention prerequisites like the column needing to exist or the path referencing a dataset.

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