get_business_acquisition

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. However, it only mentions strategic analysis and risk assessment, which are high-level outcomes, without describing the tool's actual behavior—such as whether it returns raw data, performs calculations, requires authentication, has rate limits, or is read-only. This leaves critical operational traits unspecified.

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 a single, concise sentence in Korean. It's front-loaded and wastes no words, though its abstract nature limits utility. The structure is efficient, but the content lacks actionable detail, which affects helpfulness more than conciseness.

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 complexity (3 required parameters, no output schema, no annotations), the description is incomplete. It fails to explain what the tool returns, how results are formatted, or any behavioral constraints. For a data retrieval tool with multiple inputs, this omission leaves the agent without enough context to use the tool effectively.

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 input schema has 100% description coverage, clearly documenting each parameter (corp_code, bgn_de, end_de) with examples. The description adds no parameter-specific information beyond the schema, so it doesn't enhance semantic understanding. However, since schema coverage is high, the baseline score of 3 is appropriate—the schema adequately handles parameter documentation without needing description support.

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 '영업양수 결정을 통한 사업 확장 전략 및 내부거래 리스크 분석' translates to 'Business expansion strategy through acquisition decisions and internal transaction risk analysis.' This is vague and abstract—it describes a strategic analysis rather than a concrete tool action. It doesn't specify what the tool actually does (e.g., retrieves data, generates reports, or analyzes risks). The tool name 'get_business_acquisition' suggests data retrieval, but the description fails to clearly state the verb (get/fetch/retrieve) and resource (acquisition data).

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 no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, context, or comparison to sibling tools (e.g., get_business_transfer, get_merger). Without usage instructions, an AI agent cannot determine appropriate scenarios for invoking this tool over others in the list.

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