均线交叉

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

Annotations already mark this as read-only and open-world, so the safety profile is known. The description adds meaningful behavioral context by stating that it fetches K-lines before computing crossover status and that it produces a directional bias classification, which goes beyond the annotations.

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 a single concise sentence that front-loads the tool identity and immediately lists the key output categories. There is no redundant writing or repetition of schema defaults.

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 an output schema and readOnly annotations, the description does not need to repeat return values or safety guarantees. However, given six parameters and low schema coverage, the description is thin on parameter-level context and does not help an agent decide between this and related indicator tools. It is minimally sufficient but not fully complete.

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 very low at 17%, and the description only vaguely compensates by mentioning "dual moving average." It does not explain how fast, slow, type, limit, symbol, or interval interact, nor does it clarify fast vs slow behavior. Schema fields like symbol and interval are self-explanatory, but the important indicator parameters remain under-documented.

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 a specific action and resource: it pulls K-line data and detects dual moving average crossover state, listing explicit outputs (golden_cross / death_cross / none) and bullish/bearish bias. This distinguishes it from sibling tools like indicator_sma, indicator_ema, and indicator_macd, which either return raw indicator values or use a different construction.

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 its use case: an agent should call this when the user wants dual moving average crossover detection. However, it gives no explicit when-to-use or when-not-to-use guidance, nor does it mention alternative tools such as indicator_macd or indicator_multi for similar signal detection.

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