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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description still adds non-obvious behavioral facts: only signals whose performance is confirmed after 20 trading days are counted, so the comparison window ends 20 trading days before the base date, and a missing label means the axes are too close to call. That freshness/latency caveat is exactly the kind of context annotations cannot express.

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 core question is front-loaded, then ranking content, then caveats, units, and formula — a sensible order. It is dense with domain jargon and slightly repetitive on unit conventions, but no sentence is pure filler.

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?

With no output schema, the description carries the return-value burden and does so: it explains rankings, the label derivation, unit suffixes (_pct/_pp/_krw), and the excess_pp formula. The main remaining gap is that the meaning of the 'lists' and the label naming scheme is left implicit.

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 100%, so the baseline is 3, but the description adds real meaning to `window` beyond 'comparison window (trading days, default 60)': all lists share one trading-day window and the 20-day confirmation rule shifts the effective window end. It adds nothing for `as_of` and `format`.

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 query intent — what rule/regime is currently in effect — and what is returned: per-list recent excess-return rankings plus a label read from four personality axes. It is clear enough to distinguish from per-stock or raw-signal siblings, though it never names an alternative tool or explains what the 'lists' actually are.

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?

It frames the tool as a historical-statistics lookup and adds an explicit exclusion ('과거 통계 조회 도구입니다… 특정 종목의 매수·매도 판단을 생성하는 데 사용하지 마세요'), which usefully routes agents away from trade-decision use. It stops short of naming an alternative (e.g. maedong_signal_stats) for the cases it excludes.

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