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

Beyond the readOnly/openWorld annotations, the description discloses concrete operational behavior: the paid cost ($0.002 USDC), accepted payment rails (x402 on Base, Solana, or Arc), and the fact that failed calls are not charged. It also bounds the dataset to the public page's top 1–50, which clarifies scope without contradicting annotations.

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-loads the resource and returned fields, then adds scope limits and pricing. Every sentence contributes useful selection or execution context.

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 simple one-parameter schema, readOnly/openWorld annotations, and an output schema, the description supplies everything else an agent needs: dataset boundaries, excluded content, and payment/failure semantics. No material calling context 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%, so the limit parameter is already well documented in the schema with its 1–50 range and default of 10. The description reinforces the top 1–50 scope but adds no syntax or behavioral detail beyond the schema, making the baseline 3 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 names a specific resource — the Rekt News leaderboard of the largest crypto hacks and exploits — and lists the exact fields returned (rank, incident name, audit status, loss, date). It is clear what the tool retrieves, though it does not explicitly differentiate itself from nearby crypto-data siblings such as liquidations or wallet-risk 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?

Usage is clearly implied by the leaderboard framing and strengthened by an explicit exclusion: root-cause write-ups and attack techniques are not included. It does not name an alternative sibling tool, so it stops short of full when-to-use/when-not-to-use routing.

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