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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral context — that results are partitioned by pre-launch backtest versus post-launch actual alerts with periods, and that figures reconcile with knockwatch.co.kr/record. It says nothing about update cadence, aggregation windows beyond 'period', or sample-size caveats.

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 content statement is front-loaded and compact, with the key concept (cumulative outcomes and the period split) in the first sentence. The Korean and English versions are near-duplicates, which is justified for bilingual audiences but slightly redundant; nothing is padding beyond that.

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 one optional enum parameter, no nested objects, and no output schema, the description carries exactly the burden it needs to: what the numbers mean, how they are partitioned, and that they match a known reference page. An agent has enough to call it correctly and interpret the result.

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 optional enum parameter is fully documented in the schema, including the omit-for-both behavior. The description adds no syntax, defaulting, or semantic detail beyond that, 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 specific resource and view: cumulative per-signal outcomes expressed as 'M of N cases below market', split into pre-launch historical and post-launch actual alert periods. It is clearly an aggregate-record retrieval rather than a live signal feed, which implicitly separates it from recent_signals. It stops short of naming siblings explicitly, so differentiation is inferential rather than stated.

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?

Usage is only implied: an agent can deduce this is the tool for historical hit-rate totals, and the pre-/post-launch split hints at the appropriate context. There is no explicit when-to-use, when-not-to-use, or 'use X instead' routing against check_coin, facts, recent_signals, or signal_guide.

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