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

With no annotations provided, the description carries the full transparency burden. It discloses that the answer is grounded, computed from live derivatives data, and scoped across specific venues, which is useful behavioral context. However, it does not describe output structure, request constraints, rate limits, or whether there are any side effects beyond returning an explanation.

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 front-loaded sentence with no filler. The example question and the parenthetical list of explanation components convey substantial meaning very efficiently.

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 simple 2-parameter tool with no output schema, the description communicates purpose, expected answer content, and data sources. It omits exact return formatting and symbol parameter behavior, but these are secondary given the example and the schema default.

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 0%, so the description must compensate. It adds strong semantics for 'question' with a natural-language example and describes the analytical content of the result. It does not explain how or when to set 'symbol' or what valid symbols are, though the schema default partly mitigates this.

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 this tool produces a synthesized risk-intelligence answer to a natural-language 'why' question, with concrete output components like liquidation cascades and funding extremes. It is clearly distinguished from the get_* sibling tools, which retrieve individual data slices rather than explanations.

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 gives an explicit example question ('Why did BTC drop 4%?') and describes what the returned explanation will cover, making intended usage clear. It does not explicitly name alternative tools or state when not to use it, but the contrast with raw-data sibling tools is strongly implied.

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