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

With no annotations, the description carries the full burden and does substantial work: it discloses the in-session branch semantics (preOpen = Hyperliquid at today's 08:00 open), the off-hours payload (current KRW price, US-close price, historical follow statistics, 80% band), and explicitly warns that probUp and the expected price are model output rather than a promise. It omits operational traits like latency, caching, or data freshness beyond the market-state split.

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 two modes are reasonably front-loaded, but the prose is a dense run-on mixing field paths (night.follow.ratePct, backtest.followRatePct) with domain jargon. The information earns its place, yet restructuring into short bulleted branches would make it far easier to parse.

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?

There is no output schema, so the description must convey return content, and it does list the key outputs (preOpen, current KRW price, US-close price, follow rate, 80% band, probUp, expected price). Combined with the market-state branching, an agent has enough to call it and interpret results, though exact field names and shapes remain partly 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 description coverage is 100% and the single enum parameter already documents SMSN=Samsung Electronics, SKHX=SK hynix, HYUNDAI=Hyundai Motor. The description restates the same tickers without adding new meaning about the parameter, so the baseline of 3 applies.

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 names a concrete subject (the next domestic re-open at 08:00–08:10 on KRX/NXT versus the 20:00 close) and the exact assets covered (SMSN/SKHX/HYUNDAI), so the agent knows precisely what is being predicted. It does not explicitly distinguish itself from siblings like get_arbitrage or get_convergence_history, which keeps it out of the top band.

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 implies usage by explaining the two regimes (while the domestic market trades vs. otherwise), which effectively tells the agent what it will get in each situation. However, there is no explicit when-to-use guidance, no statement of when not to call it, and no routing to alternatives such as get_arbitrage or get_convergence_history.

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