Best supply/lending APYs for an asset across Aave, Compound, Morpho, Spark and more, ranked by yield with TVL. Send { asset, chain? }. Rate-shop where to lend. [x402 paid tool — price $0.005; POST /api/lending/rates]
| Name | Required | Description | Default |
|---|---|---|---|
| asset | No | Token symbol, e.g. USDC, ETH | |
| chain | No | Optional chain filter | |
| limit | No | Max results |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It states the tool returns APYs and TVL ranked by yield, which implies a read-only operation. However, it does not explicitly disclose safety or non-destructive behavior, leaving some ambiguity.
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?
A single, compact sentence that front-loads the core purpose and includes pricing and endpoint info. Every sentence contributes value with no redundancy.
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 and no annotations, the description adequately explains the output (APYs, TVL, ranking) and the primary input. It could mention the return format or pagination, but it is mostly complete for the tool's complexity.
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?
All three parameters have schema descriptions (asset, chain, limit). The description adds minimal extra meaning beyond the schema, such as showing the expected structure '{ asset, chain? }'. With 100% schema coverage, a baseline of 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?
Description clearly states the tool provides the best supply/lending APYs for an asset across multiple protocols (Aave, Compound, etc.) ranked by yield with TVL. This distinguishes it from sibling tools like crypto_yields, rh_yields, lending_health, etc.
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?
Description says 'Rate-shop where to lend' and 'Send { asset, chain? }', implying the tool is used to find best lending rates. It does not explicitly state when not to use or alternatives, but the context from sibling names and the clear use case provides sufficient guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Tools are organized by domain prefix (e.g., 'crypto_', 'rh_', 'snipe_'), which helps distinguish between areas. Within each domain, they serve distinct purposes, though some overlap between domains exists (e.g., price data appears in multiple groups). Overall, an agent can navigate effectively.
All tool names follow a consistent snake_case pattern with a domain prefix and a verb_noun combination (e.g., 'compliance_risk', 'rh_stock', 'snipe_honeypot'). This makes the API predictable and easy to explore.
With 159 tools, the server is extremely large. While the broad scope of web3 and utility functions justifies many tools, the count is significantly above the typical range for a coherent toolkit, potentially overwhelming agents and increasing selection error.
The toolkit covers a wide range of web3 operations: crypto, DeFi, compliance, safety, scheduling, memory, etc. There are no obvious major gaps for its intended purpose, though some niche areas might be missing.