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

With no annotations, the description carries full responsibility, and it excels by disclosing the data's nature (a daily-USD-volume proxy), output buckets (deep/ok/thin/micro/unknown), the squeeze-risk flag, and the distinction between free and premium access. It also explains how to authenticate for premium data (session_token from verify_wallet_ownership or an x402 payment proof) and includes 'Not advice' as a disclaimer. No contradictions with structured data.

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 description is concise but information-dense, covering purpose, methodology, output categories, access tiers, authentication, edge cases, and a disclaimer in just four sentences. Every sentence adds value, and the structure flows logically from question to proxy to buckets to access tiers to caveats.

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?

Given the tool's moderate complexity and lack of an output schema, the description provides enough context for an agent to understand what the tool returns: a bucket category, a squeeze-risk flag, and potentially an exact volume figure for premium users. It also addresses the 'unknown' edge case and notes the watchlist dependency. This is complete for the likely use cases.

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%, so the description must compensate. It explains that ticker refers to a token, session_token comes from verify_wallet_ownership, and payment is an x402 proof, thereby adding meaning beyond the bare schema. It doesn't detail the exact format of payment or the expected ticker format, but the provided guidance is sufficient for a user to understand the parameters' roles.

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 description opens with a direct question 'How liquid is a token — can you size into it without moving the price?' which clearly establishes the tool's purpose as a liquidity assessment. It specifies the resource (token) and the core output (liquidity bucket), distinguishing it from sibling tools that focus on buzz, attention, or other metrics.

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 description provides clear context on when to use the tool (when checking token liquidity) and explains the free vs. premium tiers, including how to unlock the exact volume via session_token or payment. It also notes that 'unknown' means the token is off the watchlist, which implicitly tells the user when the tool may not provide useful data. However, it does not explicitly mention alternatives among sibling tools.

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