DeFi LP yield opportunities on Robinhood Chain: pools ranked by estimated fee APR (fee tier x 24h volume / liquidity), with liquidity and volume. Send { limit?, minLiquidityUsd? }. Yield discovery for agents providing liquidity on Robinhood's L2. [x402 paid tool — price $0.02; POST /api/rh/yields]
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max pools, default 15 (max 50) | |
| minLiquidityUsd | No | Minimum pool liquidity in USD (default 10000) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the tool is a paid x402 tool with a price of $0.02 and endpoint POST /api/rh/yields. However, it does not explicitly state whether the tool is read-only or has side effects, nor does it provide authentication or rate limit details. The description implies a read-only yield discovery, but not explicitly.
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 concise: two sentences plus a brief note about pricing and endpoint. It front-loads the core purpose and metric, then provides parameter hints and context. No superfluous words.
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?
The description provides context: Robinhood Chain L2, yield discovery for liquidity providers. It outlines the ranking metric and includes parameters. Without an output schema, it partially explains the return (pools with liquidity and volume). It is fairly complete for a simple discovery tool, though a bit more detail on the output structure would improve it.
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 both parameters already described in the schema (limit with default 15 max 50, minLiquidityUsd with default 10000). The description merely restates 'Send { limit?, minLiquidityUsd? }', adding no additional meaning beyond what the schema provides. 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 the tool's purpose: providing DeFi LP yield opportunities on Robinhood Chain, ranked by estimated fee APR. It specifies the resource (yield opportunities) and the metric (fee APR), which distinguishes it from generic yield tools like crypto_yields.
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 mentions the optional parameters (limit, minLiquidityUsd) and that it's a paid tool, but it does not provide explicit guidance on when to use this tool versus alternatives (e.g., when to use rh_yields vs crypto_yields or other Robinhood tools). The context of 'Yield discovery for agents providing liquidity' implies usage, but lacks when-not or alternative references.
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.