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

With no annotations, the description carries the full burden and delivers: it names the data sources (Lighter and Hyperliquid builder markets), the row granularity (one row per underlying), and the exact fields returned (mark, open interest, 24h volume, funding APR, cross-venue price gap in bps). It omits auth requirements, rate limits, or pagination, but the operational shape of the read is well disclosed.

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 scope and required context are front-loaded, and the alternative-route sentence is placed last where it belongs. The prose is dense but every clause contributes (coverage list, data source, row granularity, field list, filter values, sibling exclusion), with the leading '[measured]' tag being the only questionable element.

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?

There is no output schema and no annotations, yet the description still communicates the return structure (one row per underlying with per-venue metrics) and documents the sole parameter, which is more than adequate for a one-param filtered list tool. Only absent pagination/row-limit behavior keeps it from a 5.

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 the schema types asset_class only as a bare string, so the description does the essential work by enumerating the valid filter values (equity | crypto_equity | etf | index | commodity | fx | rates | preipo). This is meaning that exists nowhere in the structured data.

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 (get) and resource (tokenized stocks) and immediately bounds the scope: tokenized stocks, indices, ETFs, commodities, FX, rates and pre-IPO names traded as PERPS on specific DEXs. It is clearly distinguishable from siblings like get_stocks (non-tokenized equities) and get_hl_builder_markets (raw HIP-3 list).

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 routes the agent to an alternative: 'Use get_hl_builder_markets for the raw Hyperliquid HIP-3 list by dex,' which defines when not to use this tool. However, it does not clarify its relationship to the other closely related sibling, get_stocks, leaving one boundary to inference.

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