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

Annotations already establish read-only, idempotent, non-destructive behavior, and the description adds real substance on top: the ranking direction, annualization, the market-wide aggregate fields returned, and the $1M open-interest cutoff. It does not discuss data freshness or update frequency, which would round this out.

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?

Three sentences, front-loaded with what is returned and how it is ordered, followed by the exclusion rule and usage trigger. Every sentence contributes information; nothing is redundant with the title.

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 compensates well by enumerating the return content (ranked rates plus median, OI-weighted average, positive/negative counts) and the ranking filter threshold. An agent has everything needed to call and interpret this tool.

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 single 'detail' parameter has 100% schema description coverage with an enum explaining the brief/full tradeoff, so the schema carries the burden. The description adds no parameter-level detail, which is acceptable at this coverage level but earns only the baseline.

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?

States a specific verb and resource (returns Hyperliquid perpetual funding rates) plus the exact ordering (highest to most negative, annualized) and the payload (market-wide summary stats). This is clearly distinguishable from siblings like get_liquidation_levels or get_whale_positioning, which cover entirely different 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?

Explicitly names the triggering user intents: 'which markets pay the highest or most negative funding' and 'how funding looks across Hyperliquid.' No alternative tool or exclusion case is named, but none of the siblings is a plausible substitute, so the routing guidance is clear.

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