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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is partly covered. The description adds substantial context beyond them: deterministic rule-based behavior ('same token, same answer'), the underlying data sources (GoPlus, on-chain checks, DEX liquidity), and a cost/access constraint ('Paid ($0.01, x402)'). This is real behavioral disclosure, though rate limits and latency are unaddressed.

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 core question and answer format, then supporting facts, sources, and cost. Dense but every fragment carries information. The chain list and payment note are slightly list-like rather than prose, but 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 carries the burden of describing returns, and it does so concretely (verdict tiers, score, top 3 reasons, good signals, key facts like honeypot/taxes/liquidity/holders/owner). Supported chains and the payment requirement are stated. Only the precise response structure and error/pagination behavior are left unspecified.

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%, so chain, address, and card are already documented in the schema. The description reinforces this by listing the supported chains and explaining that the optional card yields a 1200x630 SVG, but adds little syntactic or semantic detail beyond what the schema states. Baseline 3 applies when the schema does the heavy lifting.

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 opening question 'Should I touch this token?' plus the explicit output list (verdict, 0-100 score, top 3 reasons, good signals, key facts) makes the verb and resource unmistakable. It clearly produces an assessment of a token. However, it never distinguishes itself from the sibling tools token_audit and token_report, so an agent must guess which one to pick.

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?

'Should I touch this token?' implies the decision-making context (should I interact with this token), which is genuine implied usage. But it offers no explicit when-to-use versus token_audit/token_report, no exclusions, and no prerequisites beyond the payment note. Usage is inferable but not guided.

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