get_individual_compensation

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 mentions analysis of 'compensation concentration and insider risk,' which suggests read-only, analytical behavior, but doesn't clarify if it performs calculations, returns raw data, requires specific permissions, has rate limits, or what the output format might be. This leaves significant gaps in understanding how the tool behaves in practice.

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 that efficiently states the tool's analytical purpose. It's front-loaded with the core function and avoids unnecessary details. However, it could be slightly more structured by explicitly separating the action from the outcome, but overall, it's well-sized with no wasted words.

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 complexity implied by 'analysis' and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a report, calculated metrics, or raw data), how the analysis is performed, or any behavioral traits like error handling or data sources. For a tool with analytical claims and no structured output, more context is needed to understand its full functionality.

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, bsns_year, reprt_code) with examples and codes. The description adds no additional parameter semantics beyond what the schema provides, such as explaining how these inputs relate to the analysis described. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 states the tool analyzes 'compensation concentration and insider risk through individual executive compensation details,' which provides a general purpose but lacks specificity about what the tool actually does (e.g., retrieves, calculates, or reports data). It distinguishes from siblings like 'get_executive_compensation_approved' or 'get_total_compensation' by focusing on individual details, but the verb 'analyzes' is vague compared to more concrete actions like 'retrieve' or 'calculate.'

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?

No explicit guidance is provided on when to use this tool versus alternatives. While the description implies it's for analyzing individual compensation details, it doesn't specify prerequisites, context (e.g., for risk assessment vs. compliance reporting), or direct comparisons to siblings like 'get_individual_compensation_amount' or 'get_executive_compensation_by_type.' Usage is implied but not clearly articulated.

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