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

With no annotations, the description carries the full burden and does substantial work: it discloses data provenance (10,000 largest accounts plus every account trading since the reader started, ~40-45% of venue OI surfaced in covered_long_pct/covered_short_pct) and stresses 'Not a model.' It stops short of stating auth needs, rate limits, or refresh cadence, so not a 5.

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?

Front-loaded with the '[measured, RISK AHEAD, Hyperliquid]' qualifier and the core purpose in the first clause, then alternatives, then returns, then range. Dense and every clause is load-bearing, though the parentheticals make it heavier than strictly needed.

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 or annotations, so the description has to cover behavior and returns; it names the return shape ('long/short notional per bin, cumulative curves and the largest positions') and the data-coverage caveat. Adequate for a two-parameter read tool, with only auth/rate-limit context 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 coverage is 0% and neither parameter is documented in the schema, so the description must compensate. It supplies the full enum for range (12h | 1d | 3d | 7d | max), notes ±100% and a recommended value, which the schema lacks entirely. The symbol parameter is left implicit, which is the only gap.

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+resource ('REAL open positions on Hyperliquid binned by the liquidation price the exchange itself reports') and immediately names the sibling variants it is not. An agent can distinguish it from get_lighter_liquidation_map and the modeled get_liquidation_map without opening any schema.

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?

Explicit routing: 'Use this for Hyperliquid; use get_lighter_liquidation_map for Lighter and get_liquidation_map (modeled) for the CEXs.' This gives both when-to-use and the concrete alternatives, leaving nothing to inference.

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