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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds genuinely useful context beyond that: which fields are returned, that the retrieval timestamp is returned while the exchange observation time is unknown, and an interpretive caveat ('Not a prediction'). That freshness caveat is the main value-add, but the description remains thin on behavioral details like failure modes for unknown markets.

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 short sentences, front-loaded with the usage trigger, then the scope clarification, then the data-freshness caveat. No filler and no repetition of the title or annotations.

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 correctly carries the burden of naming the returned metrics and the timestamp caveat. The one residual gap is whether the asset should be a raw name or a resolved market identifier, especially given the sibling resolve_hyperliquid_market; the schema examples mitigate this enough to keep it at 4.

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?

Only one parameter (asset) exists and schema coverage is 100%, with the schema itself supplying usage examples ('Nvidia, BTC or NVDA'). The description adds no syntax, format, or resolution guidance beyond what the schema provides, so the baseline of 3 applies.

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 the specific resource (a Hyperliquid market) and enumerates the exact data it exposes: mark price, 24-hour change, funding, open interest and volume. It rules out a common misinterpretation ('not a US stock quote'), so an agent can distinguish this from stock-quote tools. It stops short of differentiating from close siblings such as get_hyperliquid_activity or get_hyperliquid_positioning.

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?

Opens with an explicit 'Use for...' trigger enumerating the data types, and adds a clear exclusion by declaring it is exchange context rather than an equity quote. No alternative tool is named for adjacent needs (e.g., wallet-level positioning), so routing to siblings is left to inference.

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