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

Beyond the annotations (readOnly, idempotent, non-destructive), the description discloses key behavioral caveats: inflow is observed on-chain and not proven to be x402 sales revenue, trend windows are limited by actual scanned span with per-window flags, and each call costs $0.005 USDC. This is exactly the kind of additional context that helps an agent set expectations. No contradiction with 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?

The description is compact but information-dense: the first sentence enumerates outputs, the second gives the intended use, and the remaining sentences convey necessary caveats and cost. No filler or repetition; each sentence earns its place.

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?

Even without an output schema, the description details the response contents (including field names like trends.scanned_days and per-window flags) and caveats about data validity. The parameter is fully documented and cost is disclosed. An agent has enough information to invoke the tool correctly and interpret results.

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 input schema provides 100% coverage of the single 'endpoint' parameter, including examples and format guidance ('host:<hostname>' vs 'mcp:<publisher>/<name>'). The description reinforces that it applies to 'one listing' but does not add meaning beyond the schema. With high schema coverage, the baseline of 3 is appropriate.

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 clearly states the tool observes on-chain revenue signals for a single listing and enumerates the exact metrics returned (USDC inflow, distinct payers, modal transfer size, payment rate, trend windows, cohort percentile). It also gives a direct use case: sizing a seller's real traction, which distinguishes it from sibling tools focused on credit, drift, payer profiles, and authenticity.

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 explicit guidance on when to use the tool: 'Use this to size a seller's real traction.' It does not name alternatives or state when not to use it, but the usage context is clear and actionable enough to route selection among the listed siblings.

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