export_to_excel

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

Annotations indicate readOnlyHint=false, openWorldHint=true, idempotentHint=false, destructiveHint=false. The description adds context about the output (saved file path) and the data types, but doesn't disclose potential side effects like file creation location, overwriting behavior, or whether it creates files on disk. It doesn't contradict annotations, but the behavioral disclosure is minimal beyond what annotations already imply.

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 with a brief purpose statement, use cases, and a clear Args/Returns section. It's slightly verbose with the use-case bullet points, but every sentence adds value. The front-loaded purpose and structured parameter documentation make it easy to scan.

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's moderate complexity (4 params, 1 required, no enums) and the presence of an output schema, the description covers the essential context: what it does, when to use it, parameter meanings, and return value. It lacks details like file format specifics or error conditions, but for an export tool with a simple contract, it's reasonably complete.

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 compensate. It does: it explains data_type values (chart/flow/financial), code format (6-digit Korean stock code), days default (180), and filename auto-generation. This adds significant meaning beyond the bare schema, though it doesn't specify constraints like days range or filename extension rules.

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 purpose: saving single-stock data to an Excel file, with specific use cases (uploading to other AIs or analyzing in Excel). It distinguishes itself from sibling tools like scan_to_excel and save_analysis_to_excel by focusing on single-stock data export, though it doesn't explicitly name those alternatives.

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 for when to use the tool (exporting single-stock data for external analysis or AI upload) and lists the data types (chart, flow, financial) that define its scope. It doesn't explicitly state when not to use it or name alternative tools, but the use cases and data_type options give sufficient guidance for an agent to select it appropriately.

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