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

No annotations, so the description carries the full behavioral burden; it does well on what data comes back, including the derived kimchi premium. It says nothing about data freshness, provider limits, or what happens when only one of the two exchanges has the pair, which matters for an agent acting on arbitrage signals.

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?

Two sentences: the return payload first, the use case second. No filler or restatement of the title beyond what is needed.

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?

An output schema exists, so the description is right not to enumerate return fields in detail. However, for a tool whose only input is undocumented in both schema and prose, the definition leaves the caller guessing how to specify which coin to price.

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 0% for the single `symbol` parameter, and the description never mentions it — not the expected format (ticker like "BTC"), not that it defaults to BTC, not which quote assets are supported. The description must compensate here and does not.

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?

States a specific resource (a coin's KRW price) with named venues (Upbit, Bithumb) and the exact metrics returned (24h change, high/low, volume, kimchi premium). The Korea/kimchi framing cleanly separates it from generic siblings like exchange_ticker or crypto_token_prices.

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?

"Use for Korea arbitrage signals and local pricing" gives clear positive usage context. It stops short of stating exclusions (e.g., use exchange_ticker for non-Korean venues), so an agent must still infer when not to call it.

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