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

With no annotations, the description carries the burden. It discloses that the data is public (no auth) and that no proposal is required, which is real behavioral context for a read tool. It stops short of anything about rate limits, caching, or how large the unfiltered result set can be before pagination matters.

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 sentences, both earning their place: the first front-loads what is returned, the second front-loads the safety/authorization posture. Zero filler.

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 simple paginated list tool with all three parameters documented and no output schema, the description compensates by naming the returned fields. Complete enough to call correctly, though a note on ordering or default sort would close the remaining gap.

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%, with limit, offset, and search each documented including defaults and max. The description adds no additional meaning about filtering or pagination interplay, 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 ('List Hyperliquid perpetual markets') and enumerates the data returned: mark/mid/oracle prices, funding, open interest, 24h volume. It does not, however, distinguish itself from closely named siblings like screen_hyperliquid_markets, rank_hyperliquid_markets, or get_hyperliquid_market, so an agent must infer the split.

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?

'Public data; no proposal.' implies this is a read-only lookup requiring no governance proposal, which is a useful hint against the many propose_* siblings. But there is no explicit guidance on when to choose this over screen_hyperliquid_markets, rank_hyperliquid_markets, or get_hyperliquid_market.

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