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

With no annotations, the description carries the full burden and largely meets it: it discloses the return shape (as_of, cache_age_s, rows, top/bottom 5), signals that results are cached (cache_age_s), and states the access cost/mechanism ('$0.009 USDC via x402'), which is critical auth/payment context an agent cannot infer from the schema. It does not cover rate limits or refresh semantics, so it stops at 4 rather than 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 purpose, then usage, then input/output contracts, then a concrete example — a sensible order with no wasted sentences. The appended pricing sentence is useful but sits awkwardly at the tail after the example, which slightly muddies the structure.

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 the description compensates by enumerating the returned fields and envelope keys. Combined with the disclosed payment mechanism, an agent has enough to call it correctly, though cache/refresh semantics and failure behavior remain undescribed.

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 100%, so the schema already documents all seven parameters, and the description's parameter recap ('sort, order, limit (1-50), min_oi_usd, min_volume_usd, funding, min_abs_apr') largely repeats it. The one added detail is the example query string (?sort=funding&limit=20), which is marginal, so baseline 3 is correct.

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 opening sentence names a specific verb+resource+scope: a funding-rate screener over ALL Hyperliquid perps, ranked by funding, open interest, volume, basis or Binance/Bybit spread. That scope ('all perps', 'ranked by') distinguishes it from a single-market sibling like hl_perp_metrics without the agent needing to open either 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?

It gives a clear use case ('Use when hunting funding extremes or carry trades'), which is exactly the intent that would select this tool over a generic perp-metrics call. It stops short of naming alternatives or stating when not to use it, so it falls just below the explicit when/when-not/alternative bar.

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