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

Annotations already cover read-only, idempotent, and non-destructive behavior, so the safety profile is clear. The description adds meaningful behavioral context: data is produced by a discovery engine running every few hours, it decodes DLMM liquidity instructions and scores completed round trips, and it includes pricing/rate-limit details (10 free/day). This goes beyond what annotations alone provide.

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 sentences with no filler: the first front-loads the tool's purpose and ranking metrics, the second explains the data source and methodology, and the third conveys relevance and pricing. Every sentence earns its place.

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 simple read-only ranked list with one optional parameter, the description is nearly sufficient: it specifies ranking dimensions, data provenance, freshness, and pricing, while annotations cover safety. It doesn't describe the output shape, but there is no output schema and the ranked metrics make the return intent clear.

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 single 'limit' parameter is well constrained in the schema (default 10, min 1, max 25), but the description never mentions it. With schema description coverage at 0%, the description does not compensate by explaining what the parameter controls or how to choose a value.

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 names the resource ('Meteora DLMM liquidity providers') and the primary behavior (ranked by measured on-chain edge) with an explicit list of ranking metrics. It lacks an explicit verb like 'list' or 'get' and doesn't name sibling tools to differentiate, but the ranking intent is unmistakable.

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 description provides useful context about provenance and relevance ('These are the wallets our live copier watches'), but it never states when to use this tool versus siblings like dlmm_pool, dlmm_positions, or smart_money. No alternatives or exclusions are mentioned, so usage guidance is only implied.

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