get_records_preview

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

With no annotations provided, the description carries the full burden and handles it well. It discloses that the tool downloads or resolves FileObjects/FileSets, applies extracts and transforms, may download data for remote distributions, and that inline 'cr:data' rows are returned directly without downloads. It also explains the 'truncated' flag behavior, which is genuinely non-obvious execution context.

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 well-structured and front-loaded with the core function. The Returns section duplicates some information likely provided by the documented output schema, but each section earns its place, and the page's important warning is clearly separated.

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 description is complete for this tool's complexity: it names the necessary input record_set, describes the materialization pipeline, covers download side effects, directs users to 'list_record_sets' for IDs, and describes the outputs. The presence of an output schema reduces the burden of restating return types, and what the description adds — pipelining, download warnings, truncation — is exactly the contextual content an agent needs.

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?

All 6 parameters are already documented in the input schema with 100% schema description coverage, so the description does not need to re-explain them. It adds practical parameter guidance for 'limit' ('keep `limit` small on large datasets'), and it indirectly reinforces the 'record_set' parameter via the return description, but it does not add substantial new parameter-level meaning beyond the 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 states a specific verb and resource: it "Materializes the first records of a RecordSet by executing the data pipeline." It also clarifies that this yields actual data, equivalent to 'Dataset.records(record_set)', and is not just metadata inspection — distinguishing it from sibling tools like list_record_sets.

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 gives concrete use cases: 'preview/sample a dataset's actual data before writing training code' and 'sanity-check that a generated Croissant description produces the expected columns and values.' It does not explicitly name alternative tools to avoid, but it clearly implies this is the data-content tool rather than structure/validation/list tools.

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