gryps_open_interest

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

No annotations are provided, so the description must fully disclose behavior. It mentions 'raw upstream shape' and 'timestamped' but does not clarify if the operation is read-only, requires authentication, or has side effects. More detail on the nature of the query (e.g., is it cached? real-time?) would improve transparency.

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, efficient sentence that conveys the tool's purpose and key characteristics. It is front-loaded with the most important information and contains no filler.

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 lack of output schema and low complexity (0 parameters), the description is fairly complete but lacks detail on the exact return format. 'Raw upstream shape' is vague; stating the structure or fields would improve completeness.

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?

There are zero parameters and the empty schema is fully covered. The description adds value by describing the output as 'aggregated', 'raw upstream shape', and 'timestamped', which provides context beyond the schema. Baseline is 4 for no parameters, and the description justifies it.

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 it provides an 'aggregated open interest snapshot' for the venue, specifying 'raw upstream shape' and 'timestamped'. This distinctively separates it from sibling tools like gryps_get_funding (funding rates) and gryps_get_market (market data).

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?

While the tool's name and description imply it's for open interest data, there is no explicit guidance on when to use it versus alternatives, nor any prerequisites or exclusions. The sibling names provide some context but the description itself lacks usage directives.

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