kr-crypto-intelligence

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the tool is 'AI-powered' and returns an 'AI-generated signal,' which adds useful context about its analytical nature. However, it lacks details on rate limits, error handling, or authentication requirements, and the price mention hints at a transactional aspect but doesn't fully clarify operational constraints.

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 efficiently structured in a single sentence that front-loads the core purpose ('AI-powered Korean crypto market analysis') and then lists all integrated data sources and outputs. Every element (e.g., data sources, return values, price) adds value without redundancy, making it highly concise and well-organized.

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?

Given the tool's complexity (aggregating multiple data sources with AI analysis) and the presence of an output schema, the description is mostly complete. It details all input data sources and output components (signal, confidence score, etc.), and the output schema likely covers return values. However, it could better address behavioral aspects like cost implications or usage limits to be fully comprehensive.

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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the input requirements. The description adds no parameter-specific information, which is acceptable given the absence of parameters. A baseline of 4 is appropriate as it doesn't need to compensate for any gaps, but it doesn't enhance beyond the schema's completeness.

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 explicitly states the tool performs 'AI-powered Korean crypto market analysis' and lists all specific data sources it combines (Kimchi Premium, stablecoin premium, etc.), making the purpose highly specific and comprehensive. It clearly distinguishes from sibling tools like get_kimchi_premium or get_fx_rate by aggregating multiple metrics into a unified analysis rather than returning individual data points.

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 implies usage context by specifying it's for 'Korean crypto market analysis' and includes a price, suggesting it's a paid service for comprehensive insights. However, it doesn't explicitly state when to use this tool versus alternatives (e.g., vs. get_kr_prices for just prices), nor does it mention any prerequisites or exclusions, leaving some ambiguity.

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