csv_large_fields

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

With no annotations, the description must disclose behavioral traits, but it only states the action of listing fields and a supporting use case. It does not indicate that the tool reads the file, samples rows, or returns only field names, nor does it mention any side effects. The description is not misleading, but it is thin on behavioral detail, such as whether it is read-only and how results are presented.

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 two crisp sentences, front-loaded with the primary action and containing no filler. Every word earns its place, and the reference to csv_inspect is efficient.

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 has 3 parameters and no output schema; the description explains the purpose and relationship to csv_inspect, but does not describe the return format or sampling behavior. The presence of sampleRows and threshold parameters hints at behavior, but the description doesn't explicitly state that the output is based on a sample, nor does it state expected results. For moderate complexity, this is adequate but leaves gaps.

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 covers all three parameters with descriptions, so the baseline is 3. The description adds concrete examples of large values (base64 images, JSON blobs) that clarify the 'threshold' semantics, providing context beyond the schema's generic 'character length threshold'.

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 ('list') and identifies the resource ('fields in a CSV') with a clear scope ('that contain large values'). It also differentiates from sibling tools by referencing csv_inspect and noting a specific use case (identifying fields that were truncated).

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 a clear context for use by stating it 'helps identify which fields were truncated in csv_inspect', implying it's a follow-up diagnostic to that tool. It doesn't explicitly mention when not to use or alternative tools, but the intended scenario is clear. It lacks exclusion criteria, but the guidance is more than implied.

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