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

With no annotations, the description carries the full burden. It usefully discloses the score range, the signal sources, and the optional AI narrative, but omits behavior around required inputs, data freshness, fallbacks, or output structure. This is partial transparency with notable gaps.

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?

One compact, front-loaded sentence conveys the core purpose and output range without fluff. The only redundant element is pre-pending the tool name in the description.

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?

No output schema, no annotations, and four optional parameters with only placeholder semantics. An agent cannot tell whether to supply address, token, or both, what chain values are accepted, or what the response contains. More invocation guidance is needed for correct use.

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%, but the property descriptions are generic placeholders ('Token to process', 'Address to process'). The tool description adds global context (e.g. optional AI narrative) but does not clarify the meaning of the 'ai' parameter or the relationship between chain, token, and address. Baseline 3 applies due to nominal schema coverage, but the underlying semantics are thin.

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?

States a specific output (risk score 0-100) for a token, with identifiable data sources (GoPlus security signals + DexScreener liquidity) and an optional AI narrative. This distinguishes it from many sibling token tools, though it doesn't explicitly contrast with closely related tools like token-rugcheck or token-security.

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?

Usage is implied: call when you need an on-chain token risk score. It does not explicitly state when not to use this tool or compare it to alternatives, which is a gap given the large set of token-related siblings.

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