get_funding_skew

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

No annotations are provided, so the description carries full burden. It discloses the return format as a 'sorted table' and mentions annualised rates. However, it omits details like data freshness, sources, or error handling, which would be helpful for a read-only tool.

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 concise: two sentences front-loaded with purpose and usage context, with a brief note on return format. Every sentence adds value without redundancy.

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 output schema, the description's mention of a 'sorted table' is vague. It lacks specifics on columns, which venues are considered 'major', or whether the data is real-time. For a tool with no parameters, more detail about the output 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?

The input schema has zero parameters, so the description does not need to add parameter info. The tool is parameterless, and the description's mention of 'across major venues' implies no filtering, which is consistent.

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 retrieves perpetual-futures funding rates across major venues, including the max-spread pair, and notes they are annualised. This distinguishes it from sibling tools like get_sentiment_snapshot or get_consolidated_price.

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 explicit use cases: assessing perp-perp arbitrage conditions, basis trades, and overall positioning skew, with a hint that high spread indicates stretched positioning. It does not explicitly state when not to use, but the context is clear.

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