Trending / hottest pools on a chain right now, ranked by volume and momentum, with price change, volume, and liquidity. Send { chain, limit? }. Supports Base, Solana, Ethereum, Arbitrum, BSC, and Robinhood Chain. Momentum discovery for trading agents chasing volume. [x402 paid tool — price $0.005; POST /api/snipe/trending]
| Name | Required | Description | Default |
|---|---|---|---|
| chain | No | Chain, default base | |
| limit | No | Max pools, default 15 (max 50) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It reveals cost ($0.005), supported chains, and the HTTP method (POST). However, it does not explicitly state whether the tool is read-only or if it modifies state, which is important for safety assessment.
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 relatively concise with three sentences plus a pricing note. The first sentence clearly defines output, and the second gives usage. The momentum discovery sentence adds context but is slightly redundant. Overall no wasted content.
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 tool's simplicity (2 optional parameters), the description covers purpose, usage, supported chains, cost, and output nature. It lacks explicit return format details, but the output is likely straightforward. No output schema exists, so completeness is adequate.
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%, and the description adds value by enumerating supported chains (Base, Solana, etc.) and indicating default limit values. This goes beyond the schema's basic type descriptions.
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 it retrieves trending/hottest pools ranked by volume and momentum, with price, volume, and liquidity data. It distinguishes from siblings like snipe_newpairs or snipe_search by specifying 'trending' and 'ranked by volume and momentum'.
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 implicit usage guidance ('momentum discovery for trading agents chasing volume') and lists supported chains. It does not explicitly state when to avoid this tool or mention alternatives, but the context of sibling tools makes it somewhat clear.
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.