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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds that the tool analyzes shifts across 10-year and yearly luck cycles, which is useful behavioral context but not extensive.

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 two sentences with no filler: it states the core subject, then adds an explicit usage signal. Every phrase earns its place.

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 rich input schema, output schema, and safety annotations, the description is sufficient for an agent to select the tool. It lacks only an explicit relationship to sibling tools or a note about output shape, but those gaps are minor given the structured context.

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 100%, so all 15 parameters are documented in the schema. The description adds no parameter-level detail, and it does not need to because the schema already carries the full burden.

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 a specific subject matter — Yin-Yang ratio and climate (調候) balance — and how it shifts across luck cycles. It also gives concrete query examples ('is my chart hot or cold', '조후 분석'). However, it does not explicitly differentiate this tool from the sibling ohaeng_balance, so it stops short of full sibling 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 clear use guidance with quoted user intents ('is my chart hot or cold', '조후 분석'). It does not mention when not to use the tool or name alternatives, so it is clear context without exclusions.

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