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

The description adds meaningful behavior beyond the annotations: known_bad is null and never false for unknown creators, the underlying data is a batch export with a freshness lag, and each response carries its generation timestamp. These are valuable details for interpreting results correctly.

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 yet information-dense, front-loading the core purpose before adding usage guidance and edge-case semantics. Every sentence contributes: what it returns, when to use it, the null convention, data staleness, and response timestamp.

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 two-parameter lookup with no output schema, the description covers the response fields, the null semantics, the data freshness caveat, and the use case. This is enough for an agent to invoke the tool and interpret the result correctly without additional context.

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%, and the schema already explains the creator and chain parameters clearly. The description does not add new input-parameter meaning; it focuses on output semantics and usage context, so 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 states a specific query-and-answer behavior: given one creator, it returns a known-bad verdict plus rug rate, chain baseline, and the justifying multiple. It also distinguishes itself from siblings by emphasizing it is the cheapest call and returns a decision rather than a wallet list.

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?

It explicitly says to use this tool when all you need is the decision rather than the wallet list, which provides clear selection guidance versus sibling tools. It also discloses the batch-export freshness limitation, telling agents not to rely on it for creators launched in the last hour.

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