export_us_to_excel

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

Annotations indicate readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=true. The description adds that the tool consumes no tokens ('토큰 소비 없음') and has no row limit, which is useful behavioral context. It doesn't fully describe file output details, but the annotations already cover the safety profile, and the description adds meaningful context beyond them.

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 front-loaded with the core purpose, then examples, then usage guidance, then parameter details. It is slightly dense with mixed Korean/English but every sentence earns its place. The parameter list is clear and scannable.

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 has an output schema and annotations, the description covers the key context: what it does, when to use it, parameter semantics, and a key differentiator (no token consumption, no row limit). It doesn't mention file format details or where the file is saved, but the output schema likely covers return values, and the description is sufficient for an agent to select and invoke it correctly.

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 ticker with examples, period with allowed values and default, interval with allowed values and default, and filename with auto-generation behavior. This is strong compensation for 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 purpose: exporting US stock long-term data to an Excel file, with examples ('AAPL 10년치 CSV 저장', 'TSLA 5년 일봉 엑셀'). It distinguishes itself from get_us_chart by noting the 500-row limit and positioning this tool for unlimited rows, backtesting, CSV, and AI uploads.

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 says when to use this tool vs get_us_chart: when long-term data is needed and get_us_chart would truncate at 500 rows. It also gives use cases (backtesting, CSV, other AI uploads). This is strong routing guidance.

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