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

Beyond the read-only and open-world annotations, it discloses the exact $0.10 charge, x402 payment mechanism, USDC-on-Base settlement, absence of free calls, and no charge for failures. It also clarifies that buy/sell testing is a simulation and that the report includes an AI summary and action list.

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 front-loads the purpose, then covers report scope and commercial terms without filler. Its many components are packed into one dense sentence, which slightly reduces scanability.

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 one-parameter report, it supplies the network, decision context, report contents, pricing, payment requirements, and failure-billing behavior. Despite the absence of an output schema, the component inventory, AI summary, and what-to-do list give the agent a reasonable expectation of the result.

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 schema fully documents the sole address parameter, including its Base token-contract meaning and 0x address pattern. The description adds no further parameter validation or handling details, so the high-schema-coverage baseline 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?

It clearly defines a comprehensive due-diligence report for a Base token and enumerates its token, creator, wallet, liquidity, domain, and market-collapse checks. The 'token check ... plus' framing distinguishes this aggregate report from narrower siblings such as check_token_safety and check_token_creator.

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?

'Before a bigger buy' provides a concrete use case, while the price and 'no free calls' warning discourage casual invocation. It does not explicitly direct agents to cheaper sibling tools for narrower checks, so alternative-selection guidance remains incomplete.

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