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

The annotations already establish that this is a safe, read-only, idempotent, non-destructive operation. The description adds context about what the data represents—official default rates for new BNB Chain pools after first analysis—but does not address freshness, sample size, update frequency, or output structure.

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 a single, dense sentence with no filler. It front-loads the core concept—how often pools ended in a rug pull by grade—and appends the rationale for using it.

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 zero-parameter, read-only tool with no output schema, the description sufficiently explains what the returned data conceptually represents. It could be strengthened with details about grade categories, time windows, or whether the data is current, but the core meaning is complete.

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 are zero parameters, so there is no parameter semantics burden. The schema is fully described and the description provides enough conceptual framing for a no-argument aggregate lookup.

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 identifies a specific analytical resource: historical default rates of new BNB Chain pools grouped by first-analysis grade. It is distinguishable from get_token_rating because it describes an aggregate track record rather than an individual token rating, though it does not explicitly name the sibling tool.

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 phrase 'so the reliability of the ratings can be judged' implies the intended use case, but it gives no explicit when-to-use guidance, prerequisites, or comparison to alternatives such as get_token_rating. 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.