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

Beyond the annotations (readOnlyHint=true, idempotentHint=true, destructiveHint=false), the description discloses key behaviors: deterministic construction, no LLM involvement, return content (A/B sequences, unique steps, shared steps, contrast edges), and the meaning of low a_coverage/b_coverage as an honest knowledge-thinness signal with instruction to not fabricate gaps. This adds significant context beyond the annotation fields and aligns with them; no contradiction.

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 front-loaded with the core purpose and examples, followed by concise routing rules, parameter semantics, and behavioral notes. Every sentence carries distinct, actionable information; there is no filler or redundancy. Despite being longer than the minimal two-sentence example, its density and clear formatting justify a perfect score.

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 comparison tool with a relatively rich operational model, the description covers everything needed to invoke it correctly: what it returns, how to pass parameters, the meaning of coverage fields, honesty principles, and its read-only/external-call-free nature. The output schema exists, so return-value details need not be repeated, and annotations already cover safety. No material gap remains.

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 already covers parameter meaning at 100%, including the 'A vs B' option in parameter a. The description adds important usage semantics beyond the schema: parameters are concept/method names rather than question sentences, the separator is strictly 'vs', and leaving b empty when only one side is given produces no useful result. This elevates the baseline of 3 to a 4 by providing operational guidance that prevents misuse.

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 verb and resource: it contrasts differences between two methods/concepts, with concrete examples ('RC 구조 vs 조적조', '스틱 vs 유닛 커튼월'). It also explicitly differentiates itself from sibling tools by naming scenario, enumerate, define, and k_snippets as alternatives for other request types, so the agent can clearly distinguish when to use compare.

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 gives explicit 'call it for comparison/difference requests' guidance and lists when-not-to-use with specific alternative tools ('단일 순서는 scenario · 종류 열거는 enumerate · 용어 뜻은 define · 수치·조문은 k_snippets'). It also provides critical parameter usage rules: a and b are concept/method names, not question sentences, and how to handle the 'A vs B' format, including the warning that providing only one side yields no comparison.

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