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

Beyond the readOnly/openWorld annotations, it discloses genuine behavioral facts the structured fields do not: the data provenance ('large accounts' public positions'), that results are aggregated and signed, the specific risk flags emitted (long_cascade_risk, short_squeeze_risk, thin_book), and the per-call cost ($0.02 USDC via x402 on Base or Solana). Cost and provenance are exactly the kind of context an agent needs before invoking a paid call.

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 'Use before...' framing is front-loaded and the body is dense with substantive detail rather than filler. The trailing clipped fragments ('Aggregates only. Signed. Not investment advice.') read as boilerplate and slightly dilute the structure, but nothing materially wastes space.

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?

For a single-parameter, read-only aggregate tool with no output schema, the description covers everything an agent needs: what is computed, the data source, the flags returned (compensating for the absent output schema), and the price model. No material gaps remain.

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 exists and schema coverage is 100%, with the schema itself supplying the case-sensitivity note and examples (BTC, ETH, SOL, HYPE, kPEPE). The description adds no format or semantics beyond 'one perp', so this sits at the baseline for a fully documented single parameter.

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 title and description state a specific verb+resource: liquidation levels and order-book depth for a single Hyperliquid perp, including what is computed (longs liquidating 1-20% below mark, shorts above, clusters, OI coverage vs depth/spread/slippage). Scope is clear ('one perp', 'from large accounts') but the description never names the sibling it differs from (e.g. liq_market for market-wide liquidation data), leaving differentiation to inference.

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 a clear usage window: 'Use before opening, sizing or holding a Hyperliquid perpetual position.' That is strong positive context. It offers no when-not guidance or explicit alternative tool, which keeps it out of 5 territory.

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