Top movers: OI spikes, extreme funding, widest basis, highest stress

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

The annotations already declare this as a read-only, open-world operation, so the description's most valuable addition is the output shape: four top-10 lists returned in one call. That tells the agent this is a batch summary rather than a paginated or single-result query. It does not state freshness or refresh cadence, which keeps it below a 5.

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?

Two sentences, both earning their place. The use-case triggers come first, and the return shape is stated last in a single compact clause.

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?

With no parameters and no output schema, the description must carry the return-shape burden, and it does at a high level by specifying four top-10 lists. It doesn't enumerate exactly what fields each list contains, but that is a minor gap for a screening tool whose title already names the four dimensions.

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?

This tool takes zero parameters, so there is nothing for the description to disambiguate. The baseline for a no-parameter tool applies, and the description correctly avoids inventing parameter-like 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 names a specific capability: a screener that surfaces four derivative market extremes (OI changes, funding, basis, stress) in one call. That is clearly distinguishable from single-metric siblings such as get_open_interest or get_funding_heatmap because it advertises an aggregated cross-metric view rather than one series.

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?

It gives concrete trigger phrases ('what is moving in crypto derivatives right now', biggest OI changes, extreme funding, widest basis, highest stress), which maps directly onto user intents. It does not explicitly name which sibling to use instead for a single-metric deep dive, but the intended usage context is unusually clear.

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