Market Detail

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

The description discloses significant behavioral detail beyond the annotations: it warns that the raw API priceChange field is unreliable, explains that 24h stats are computed from 25 x 1h candles, gives the exact basis formula, and documents error behavior for unknown/delisted tickers. These are exactly the kind of non-obvious behaviors that help an agent use the tool correctly.

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 information-dense but well organized: a one-sentence summary up front, then the returned fields, then error behavior, then an example. Every sentence contributes either to what the tool does, how it computes values, or how to call it. No filler or repetition.

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-parameter tool with an output schema present, the description is complete. It explains the input, the returned fields, the derivation logic, the reliability caveat, and the failure mode for invalid inputs. An agent has everything it needs to select and invoke this tool correctly.

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 only defines ticker as a string with zero description coverage, so the description must compensate. It does by providing a concrete example, market_detail(ticker="BTC-USD"), and by explaining that the ticker must refer to a currently served perpetual market. It could be even more explicit about ticker format rules, but for a single required parameter the example is sufficient guidance.

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 opens with 'One perpetual market in depth,' naming the exact resource and scope, then enumerates the concrete data returned: prices, 24h stats, OI, funding, candles, and basis. This makes the tool's purpose unambiguous and distinguishes it from list-level tools like list_markets and from pure candle history tools like candles. The example call reinforces the intended usage.

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 first sentence gives clear context for when to use the tool: when you need detailed stats for a single perpetual market. It also provides a useful negative constraint by stating that unknown or delisted tickers raise an error and that settled markets are not served. However, it does not explicitly name sibling alternatives or state when to prefer one of those instead.

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