binance_futures_24hr_ticker

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

With no annotations, the description carries full burden and addresses key behavioral traits: it discloses that stats use mark prices to avoid anomalous fluctuations, explains funding fee direction, and highlights leverage effects. It also provides a comprehensive output example showing the exact data shape. However, it does not explicitly state that the operation is read-only, which is implicit but could be clearer.

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 highly structured with emojis, clear sections, and a detailed output example, making it easy to parse. However, it is somewhat verbose—some sections like '市场分析' and '交易提示' extend beyond essential tool behavior and into advisory content, which could be trimmed for token efficiency.

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 absence of an output schema, the description compensates with a thorough example output covering price, volume, funding rate, open interest, and analysis. It also explains use cases and important metrics, making it complete for a market data tool. Minor gaps exist around error cases or rate limits, but these are not critical for this type of tool.

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 already provides 100% coverage with a clear description and examples for the symbol parameter. The description does not add further parameter-level detail, but since the schema is sufficient, a baseline score of 3 is appropriate.

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 it retrieves 24-hour market statistics for perpetual futures contracts, including price change, volume, funding rate, and open interest. It distinguishes itself from spot by explicitly noting it provides richer data, making it distinct from sibling tools like binance_spot_24hr_ticker.

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 '适用场景' section provides clear contexts: futures traders analyzing opportunities, arbitrage traders monitoring spot-futures spread, risk managers evaluating volatility, and fund managers analyzing funding rates. It lacks explicit 'when not to use' or naming alternatives, but the scenarios effectively imply when this tool is appropriate vs spot equivalents.

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