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

Annotations cover read-only/open-world safety, and the description adds genuinely new behavioral facts: ranked output, historical base rates attached, signed results, a disclaimer, and notably the x402 payment cost ($0.02 USDC on Base or Solana). The payment/auth requirement is a real operational trait not captured by annotations.

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?

A single dense paragraph, front-loaded with the tool's purpose before secondary facts (filter, signature, disclaimer, price). Every clause carries information, though the parenthetical enumeration is long.

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?

With no output schema, the description usefully explains the return shape (ranked by 7-day move, each with base rates), and covers filtering and cost. It is nearly complete for a read-only listing tool.

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?

The single state parameter has 0% schema coverage, so the description must compensate. The parenthetical enumerating the seven state categories maps directly onto the enum values, giving an agent the meaning of each filter option even though the exact enum strings aren't quoted.

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?

Names a specific resource (Hyperliquid perps) and precisely defines the 'crowd state' condition set with the exact thresholds (50/100/200%, funding top/bottom 5%, attention spikes, new listings). An agent can tell this is a market-wide state-scan rather than a per-symbol tool like crowd_perp.

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?

The optional ?state= filter implies how to narrow results, but there is no explicit when-to-use guidance and no routing to related siblings (crowd_perp, crowd_market, crowd_changes). Usage is inferable rather than stated.

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