describe_file

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

With no annotations provided, the description carries the behavioral transparency burden. It discloses the row count behavior (can be skipped for large inputs) and the supported path types. It does not explicitly state side effects, but as a read-only describe operation, the behavior is sufficiently clear.

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 compact and well-structured: a clear opening statement, a brief list of supported formats, and an Args section. No unnecessary words or redundancy, and every sentence serves a purpose.

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 the tool only has two parameters (one required) and an output schema exists, the description is complete. It covers the purpose, supported input types, parameter semantics, and the optional row count behavior. The output schema covers return values, so no further detail is needed.

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 Args section explicitly describes both parameters: path with an example ('data/sales_*.parquet') and include_row_count with its purpose. This fully compensates for the 0% schema description coverage and adds valuable meaning beyond the bare 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 function: 'Return the column names and types of a data file, plus its row count.' This uses a specific verb ('return') and resource ('data file') and distinguishes it from siblings like query, preview_file, and profile_columns, which have different purposes.

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 clear context on applicable inputs: 'Works for any path DuckDB can read -- csv, parquet, json/ndjson, xlsx, compressed variants, globs matching many files, http(s) URLs and s3 URIs.' It also explains the include_row_count option for large inputs. However, it does not explicitly mention when to use this tool instead of siblings like preview_file or profile_columns.

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