재무제표 조회

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It fully discloses the auto-fallback from consolidated to separate statements, the exact value formats (raw/value/display), the meaning of 'change' (period-over-period, cumulative for income/cash flow), and the limitation regarding non-audited companies. This goes well beyond mere operational description and provides deep insight into expected behavior.

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 longer than typical but every bullet point adds meaningful information: defaults, cross-tool compatibility, value formats, change semantics, and limitations. It is well-structured with a clear opening sentence followed by value-adding bullets. Slightly verbose, particularly the key_metrics cross-reference which could be seen as specialized, but overall concise for the tool's complexity.

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 tool with 7 optional parameters, no output schema, and no annotations, the description is remarkably complete. It covers default behaviors, fallback logic, output structure, change basis, and validation caveats. The only omission is a detailed return schema, but the description provides enough about value formats to compensate. The cross-tool references also situate it well within the broader toolset.

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?

Input schema coverage is 100% and parameter descriptions are already detailed (e.g., unit, fs_div, statement all have defaults and explanations). The description mostly repeats schema information (e.g., fallback for fs_div, default year) rather than adding new parameter-level meaning. It does add context about how output values relate to parameters (unit conversion) but this is not substantial enough to raise the score above the baseline for full schema coverage.

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 opens with a clear and specific verb+resource statement: '단일회사 재무제표를 조회합니다' (retrieves single-company financial statements). It distinguishes itself from siblings by emphasizing '단일회사' (single-company), contrasting with get_group_structure which handles group financials. The default (most recent annual report's balance sheet) and fallback behavior further clarify the tool's exact scope.

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 explicit guidance on when to use this tool and when not to. It states that companies not subject to external audit may not have DART financials, and directly recommends using get_group_structure(include_financials=true) for conglomerate subsidiaries. It also connects key_metrics output to check_disclosure_duty inputs, giving concrete cross-tool usage context.

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