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

With no annotations, the description carries the full burden and does reasonably well: it discloses the cost model ($0.02 via x402), the direction of the score (higher = riskier), the exact signals measured, and a scope/liability caveat. It omits auth requirements, rate limits, and how long a score stays valid, but the core behavioral profile is clear.

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 the score range and direction, then factors, then usage trigger, then price and disclaimer. Every clause carries information; nothing is redundant.

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 compensates by explaining the score scale and the constituent signals. It does not describe the response shape (field names, whether the flags are booleans or sub-scores), so an agent knows what the number means but not exactly what it receives.

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?

There is a single optional parameter with 100% schema description coverage, including the AERO fallback and example=true behavior. The description adds no syntax or format detail beyond the schema, 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?

The description states a specific resource (ERC-20 token on Base) and output (0-100 risk score) plus the exact factors scored: liquidity, top-5 holder concentration, honeypot/tax flags. It does not, however, differentiate itself from sibling tools like rug_check or token_verdict, which appear to cover overlapping risk-assessment ground.

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?

'Use before buying or listing an unknown Base token' gives a clear triggering context for the tool. It stops short of naming alternatives (e.g. rug_check, token_verdict) or stating when this tool should be skipped, so the agent must infer routing from names alone.

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