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

With no annotations provided, the description carries the full transparency burden. It discloses nuanced accounting behaviors: holding counts as a loss, tokens acquired elsewhere and sold here count as a win, and no closed-position check is performed, citing an audit date. This is unusually thorough.

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 tight sentences with no filler. The core definition is front-loaded, followed by the most important interpretive warnings. Every sentence adds information.

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 single-parameter tool, the description covers the metric definition, edge-case accounting, and a known audit limitation. It does not describe the output shape or ranking direction, but 'leaderboard' makes most of that inferable.

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 description coverage is 0% and the description does not mention the 'limit' parameter at all. The schema does provide type, default, and maximum, so the parameter is still usable, but the description adds no semantic value for parameters.

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 names the exact resource (leaderboard of X1 wallets), the metric (NET XNT FLOW per token), and explicitly negates a common misinterpretation (NOT a profit and loss). This makes it clearly distinguishable from sibling leaderboard tools and from analytics tools.

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 leaderboard framing implies the use case, and the 'NOT a profit and loss' caveat helps prevent misuse. However, it does not name specific sibling alternatives or state explicit conditions for when this tool should be chosen over others like top_tokens or graviton_top_bettors.

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