preview_data

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

With no annotations provided, the description carries the full burden. It discloses what the tool does: lists sheets, column names, row count, date range, and frequency, and that it detects date parsing. The word 'preview' implies a read-only operation, but the description does not explicitly state that no modifications occur or mention any permissions. Still, the behavioral output is clearly described.

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 concise and well-structured: a one-sentence purpose, a bullet-style list of output details, a clear usage directive, and a compact parameter list. Every sentence adds value, and the most important information (what it does and when to use it) is front-loaded. There is no redundancy or filler.

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 simple tool with only two parameters and no output schema, the description covers the essential aspects: what it previews, what information it returns (sheets, columns, rows, date range, frequency), and parameter details. It also contextualizes itself relative to load_data. It could optionally describe the exact return format (e.g., a dictionary), but the listed outputs suffice for an agent to anticipate the tool's behavior.

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?

Schema description coverage is 0%, so the description must fully compensate. It does so with a Parameters section: source_path is defined as a path to .xlsx, .xls, or .csv, and sheet is described as 'sheet name (Excel only; default = first sheet).' This adds critical meaning beyond the bare schema titles 'Source Path' and 'Sheet,' making the parameters self-explanatory.

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 begins with a clear, specific statement of purpose: 'Preview the contents of an Excel or CSV file before loading.' It then enumerates the exact outputs (sheets, column names, number of rows, date range, frequency) and explicitly distinguishes itself from load_data by saying 'Use this before load_data.' This fully differentiates it from sibling tools.

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 explicitly tells the user when to use the tool: 'Use this before load_data to choose the right column and confirm that dates are parsed correctly.' This names the associated alternative and provides a concrete use case. However, it does not mention when NOT to use it, or any other alternatives, so it falls short of a full 5.

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