getCopyTradingClassicLeaderboard

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

No annotations are provided, so the description carries full burden. It explains that the endpoint returns a ranked list and that the order must be preserved. It also mentions return metrics (30-day return, drawdown, Sharpe) used for comparison. While it lacks explicit safety or auth notes, it gives sufficient behavioral context for a read operation.

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 long and includes extensive agent instructions that go beyond the tool's own behavior. While the first sentence is front-loaded, the subsequent paragraphs could be more concise. Every sentence is useful, but the length reduces scannability for an AI agent.

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 no output schema, the description fully documents the return value: a ranked list with metrics (return, drawdown, Sharpe) and the leaderMark identifier. It also explains the intended use in a conversational flow, making it complete for an AI agent to invoke and process the result correctly.

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 tool has zero parameters, so the input schema is fully covered by definition. The description does not need to add parameter information. It appropriately focuses on the return value and usage. Baseline score of 4 applies as per guidelines.

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 the tool retrieves a curated Copy Trading Classic leaderboard for conversational recommendation flows. It specifies the output is a ranked list of candidate leaders and distinguishes from the sibling getCopyTradingTradFiLeaderboard by name and usage context.

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 explicit instructions on when to use this tool (in conjunction with the TradFi leaderboard for user queries about reliable copy traders), how to present the two lists separately, and how to map selections to subsequent actions. It also tells the agent not to ask the user to repeat the leaderMark, offering clear when-not-to-use guidance.

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