get_major_decision

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

With no annotations, the description carries full burden and discloses fallback behavior and potential failure modes (empty results) when corp_code is omitted. It also implies read-only operation. However, it does not explicitly state safety or idempotency.

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 moderately concise but includes a mix of Korean and English, and the parameter explanations are embedded inline, making it slightly verbose. The main purpose is front-loaded, but the structure could be tighter.

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 an output schema exists, return values need not be explained. The description covers purpose, specific use cases, parameter details, and failure modes. It lacks general context about the data source (DART) but is otherwise complete for a 3-parameter tool.

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 coverage is 0%, so the description must compensate. It provides detailed explanations for all three parameters, including format (14자리, 8자리), a list of enum values for decision_type, and behavioral notes about corpc_code recommendation and fallback. This thoroughly adds meaning beyond the 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 it retrieves 12 types of major decision disclosures as structured fields, and mentions specific use cases like related party hollowing. However, it does not explicitly differentiate from sibling tools, though the structured field aspect implies distinction.

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 a specific use case (tracking patterns) but lacks explicit guidance on when not to use this tool versus alternatives. No exclusions or comparisons with sibling tools are given.

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