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

With no annotations, the description carries the full burden and does disclose the computational outputs and the signal's possible enum values. It does not mention data-window assumptions, exchange/symbol availability, errors, or whether this is purely read-only, but the getter name and analytical output list make major surprises unlikely.

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 one dense sentence followed by a minimal parameter list. Every phrase adds useful information, and the output enumeration is front-loaded.

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 tool with no output schema and no annotations, the description names the returned metrics and signal values, which is helpful. It stops short of full completeness by omitting return shapes, typical lookback/defaults, and any differentiation from sibling basis tools.

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 provides no descriptions for the three string parameters, so the description must compensate. It adds that exchangeA and exchangeB are the two sides of the basis spread and that symbol identifies the market, but it gives no format, allowed values, or exchange identifier conventions.

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 what the tool produces—basis regime statistics between two exchanges, including mean/std/z-score/percentiles, trend, oscillation score, and signal. It is specific about the resource and outputs, but it does not explicitly differentiate itself from the closely related get_basis_signal and get_basis_history siblings.

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 it should be used when an agent needs a quantitative regime summary and trading bias for a pair of exchanges. However, it does not state when to prefer get_basis_signal or get_basis_history instead, so the guidance is only implicit.

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