kol_leaderboard

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so safety is covered. The description adds cost information ($0.02/page) and details about the data included (lifetime realized SOL, win rate, activity window), which goes beyond the annotations. No contradictions found.

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?

The description is compact and front-loaded with the cost, followed by the core functionality and a practical use case. Every sentence carries essential information with no filler.

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?

Given the output schema exists (noted in context signals), the description doesn't need to explain return values. It fully covers what the tool does, the data it ranks, its sorting options, and a typical use case. Nothing an agent needs to call it correctly is missing.

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 each parameter explained in the schema. The description reinforces the sort values (profit, success, activity) and the recent-activity window concept, but adds no new information beyond what the schema already provides. A baseline 3 is appropriate.

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 states what the tool does: it ranks tracked KOL wallets by lifetime realized SOL, win rate, and activity, with sorting options. It also gives a concrete use case (build/refresh copy-trading watchlist). This distinguishes it from siblings like 'kol_record' which likely focuses on a single wallet's details.

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 explicitly states when to use it ('Use to build or refresh a copy-trading watchlist'), giving clear context. However, it doesn't mention when not to use it or compare with alternatives, so it stops short of the top score.

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