Describe a data file

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

The readOnlyHint annotation already marks this as safe, and the description adds meaningful behavioral insight: it reads a sample for very large files, implying approximate or sampled statistics rather than exact full-file calculations. This goes beyond the annotation and helps set expectations about result accuracy.

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?

Two sentences, no filler. The core output is listed first, and the token-efficiency/sampling note is a single concise second sentence. Every part contributes to understanding the tool.

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 profiling tool with no output schema, the description enumerates what will be returned (schema, row/column counts, per-column statistics) and mentions sampling behavior. Minor gaps include supported file formats and whether 'local' excludes remote paths, but overall the definition is sufficient for an agent to understand scope.

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 description coverage is 100%, with clear descriptions for both path and limit. The tool description reinforces that limit controls sampling, but adds little beyond the schema's existing parameter documentation. Baseline 3 is appropriate since the schema handles parameter semantics.

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 states a specific verb ('Return') and a specific resource (a local data file's schema, counts, per-column statistics). This clearly distinguishes it from siblings like preview_data (raw rows), query_data (querying), visualize_data (charts), and diff_data (comparisons). No ambiguity about what the tool produces.

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 implies when to use it: for getting a summary of a data file's structure and statistics, particularly for very large files where token-efficient sampling is valuable. It does not explicitly name alternatives or say when not to use it, but the context of profiling and sampling is clear enough to guide selection.

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