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

No annotations are provided, so the description carries the burden. It usefully discloses a paid cost ('$0.002 USDC per call'), which an agent needs for invocation decisions, but omits return format, result count, or ordering behavior beyond 'top trending'.

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?

Three short sentences, front-loaded with purpose, then value, then cost. No sentence is wasted and the pricing caveat sits at the end where it belongs.

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?

The tool is simple (one optional parameter, no annotations, no output schema), so the description is nearly sufficient. It stops short of describing what a returned trending token entry contains or how many results to expect, which would help an agent interpret output.

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 coverage is 100% with a single optional parameter already documented in the schema. The description reinforces that the chain filter is optional with an example set of values, adding mild scoping clarity beyond the schema.

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 verb+resource ('Get top trending/boosted tokens') and the source ('on DEXScreener'), so an agent can identify the function immediately. It does not explicitly contrast with near-siblings like new_pairs or dex_search, so it falls short of full sibling differentiation.

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?

'Shows what's getting the most attention right now' implies a use case (attention/trend monitoring), and 'optionally filter by chain' clarifies scoping. However, it never says when to prefer this over alternatives such as new_pairs, top_traders, or dex_search, leaving selection to inference.

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