market.kimchi_alert

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

With no annotations provided, the description carries full behavioral disclosure burden. It discloses that this is a live snapshot only, not for historical data, and defines the alert thresholds. It also sketches both success and failure return shapes, giving the agent a clear picture of what to expect.

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 well-organized into purpose, usage guidance, arguments, and return format. Every section adds needed information without padding, and the core behavior is front-loaded.

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 single optional parameter with no output schema and no annotations, the description is complete. It defines what the tool returns, the failure format, when to use it, and when to avoid it, so an agent can decide and invoke it correctly without further information.

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 schema description coverage is 0%, so the description must compensate for the symbol parameter. It does so by explaining that symbol is a ticker like 'BTC', 'ETH', or 'SOL' and noting the default value, adding meaningful guidance beyond the bare schema.

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 clearly states the tool detects Korea-vs-global crypto price arbitrage, with specific output flags for reverse-premium crash risk and premium surges. It names the exact exchange (Upbit) and the comparison target (global market), making its purpose unmistakeable and distinct from sibling tools like arb.spread_matrix.

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 explicitly says when to use the tool: for cross-exchange arbitrage opportunities in Korean crypto markets, reverse-premium crash risk, or sudden premium surges. It also explicitly says when not to use it, ruling out historical/backtesting data and non-Korean comparisons, and points to a specific alternative tool.

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