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

While annotations handle safety hints, the description adds crucial behavioral context not present in the schema: the operational cost ('Price: $0.02 USDC per call') and a technical constraint ('Never visits metadata URLs').

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 highly dense and efficient, front-loading the core function (scam check) and quickly moving to scope, limitations, and usage instructions without unnecessary filler.

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 complexity (multi-chain risk analysis, cost structure, and technical constraints), the definition provides all necessary context to a hypothetical agent to determine if and how to call the tool.

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?

With 100% schema coverage, the baseline is high. The description reinforces the purpose of the input parameters by defining the domain (Base, ETH, Solana) and the type of data expected (token contract / mint address) in the context of risk assessment.

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 tool clearly defines its purpose as performing a comprehensive scam and honeypot risk check. It goes beyond a simple 'check' by listing specific risks covered, such as checking for fake-USDC lookalikes and rug-pull indicators.

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 usage routing by mentioning the free pre-check sibling, `validate_token_check`, giving the agent clear instructions on when to use a simpler tool instead of this full, paid one.

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