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

Annotations already cover read-only, idempotent, non-destructive and closed-world, so the safety profile is settled. The description adds real value beyond that: it clarifies the data is aggregated, that no account addresses are returned, and which accounts are tracked (Buildix's tracked large accounts).

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?

Two tight sentences: the first defines the payload and privacy boundary, the second gives the usage trigger. No filler and the key scoping ('one market', 'no addresses') is front-loaded.

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?

No output schema exists, yet the description compensates by listing the returned fields (long/short notional, account counts, bias) and the privacy constraint. Annotations cover safety and the schema covers both params, so nothing needed for correct invocation is missing.

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?

Schema description coverage is 100%, and the schema already documents both 'symbol' (ticker formats, HIP-3 dex:COIN) and 'detail' (brief vs full). The description adds no parameter-level meaning beyond 'one market', so the baseline 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?

States a specific verb and resource: aggregated long-vs-short positioning of large Hyperliquid accounts for one market, and enumerates the returned fields (notional, account counts, bias). This is clearly distinguishable from siblings like get_funding_rates or get_liquidation_levels.

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?

Gives an explicit trigger: 'Use it when the user asks whether whales or large traders are long or short a coin.' It does not name an alternative tool or state when not to use it, but the intended context is unambiguous.

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