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

With no annotations provided, the description carries the full burden. It discloses key behaviors: window is ignored for oi, and `total` is the coin-level aggregate. It also details what each metric returns (e.g., long_short returns ratio and taker buy/sell volume). While it does not discuss error handling or rate limits, it transparently explains the tool's core behavior.

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 two sentences long and packs all essential information. The first sentence states the purpose, and the second lists each metric with its return details. No redundant or vague wording; every clause contributes to understanding the tool.

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 (three params, no output schema), the description covers the main aspects: purpose, metric behaviors, and the window exception. It does not describe output structure or error cases, but for a data retrieval tool, it is sufficiently complete. Sibling tools are contextually distinct, so no ambiguity remains.

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 description adds significant meaning beyond the schema. The schema only lists the metric enum without descriptions, but the description explains exactly what each metric value returns. It also clarifies the window parameter's behavior (ignored for oi). This fully compensates for the schema's lack of metric description, making parameter semantics clear.

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's function: 'How one coin's futures activity splits across exchanges.' This is a specific verb (splits) with a clear resource (coin's futures activity by exchange). It distinguishes itself from siblings by focusing on per-exchange breakdown, which is unique among the listed tools.

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 provides clear context on what each metric returns, which implies when to use this tool (when per-exchange data is needed). However, it does not explicitly mention alternative tools or exclusions, such as using get_market_overview for an aggregate market view. The guidance is understood but not directly stated.

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