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

With no annotations, the description must disclose behavior on its own. It states that results are capped at N entries and ordered by liquidity, but it does not describe the fields in each entry, whether the order is descending, or any data-freshness caveats.

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?

Two short sentences deliver the core purpose and result behavior with no wasted words. The key qualifier (by liquidity) is front-loaded before the return count.

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, but there is no output schema, so the description should clarify what an 'entry' contains. The current text leaves return-value structure and any assumptions (e.g., descending order) implicit, making it adequate but not fully complete.

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 provides only the type and bounds for n, with no description. The phrase 'Returns up to N entries' explicitly ties the parameter to the output size, which is meaningful semantic information beyond the raw 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?

The description clearly identifies the resource (tokens on X1), the ranking criterion (liquidity), and the result shape (up to N entries). This distinguishes it from siblings such as top_traders and token_lookup.

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 intended use is implied: an agent should call this when the user wants the most liquid tokens on X1. However, there is no explicit guidance about when not to use it or which sibling tool to prefer for related requests.

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