trending
[$0.002 USDC per call via x402] Top trending cryptocurrencies right now (most-searched coins, with rank, price and 24h change).
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
[$0.002 USDC per call via x402] Top trending cryptocurrencies right now (most-searched coins, with rank, price and 24h change).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the cost ($0.002 USDC per call via x402), which is useful behavioral context not in annotations (none provided). However, it doesn't disclose output size, refresh rate, or how 'trending' is determined beyond 'most-searched.' With no annotations to carry the safety profile, some burden falls on the description, which partially addresses it but lacks depth.
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 a single concise sentence that front-loads the pricing information before the purpose. It's efficient with no waste, though the pricing detail could arguably be considered extraneous in the description (it might belong in annotations or metadata). Still appropriately compact.
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 tool is very simple (0 params, no output schema), so the description need not be extensive. It states what data is returned (rank, price, 24h change). However, with no output schema, it doesn't detail how many items are returned or the exact response format, leaving some ambiguity for a tool agents will use for market data.
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?
The tool has 0 parameters, so there's no parameter semantics to document. The schema coverage is 100% (empty properties), and the description doesn't need to add parameter meaning. Baseline 4 applies for zero-parameter tools since there's nothing for the description to explain.
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 returns top trending cryptocurrencies (most-searched coins) with rank, price, and 24h change. It uses specific verbs and resource, and the naming 'trending' distinguishes it clearly from siblings like market_summary or price.
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 doesn't explicitly state when to use this vs alternatives, but the 'trending' concept and 'top trending cryptocurrencies' framing make the use case reasonably clear. No exclusions or alternatives are named, but the context of it being the trending/popularity tool among siblings is implied.
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.
Most tools are distinct by domain (market data, safety, DEX trading, yield, gas), but there is meaningful overlap: token_risk, token_score, and screener all deal with token safety/rug-pull concerns, and screener partially overlaps with trending and token_pairs for discovery. An agent picking between token_risk and token_score could be confused despite the price difference, and screener's safety screening overlaps with both.
All names follow a consistent lowercase noun pattern (fear_greed, gas, ohlc, price, yields, token_pairs, market_summary, etc.), with concise single-word or snake_case single concepts. No verb prefixes, no mixing of conventions, no camelCase. Highly predictable across the whole set.
11 tools for a crypto data API is well-scoped, covering market prices, candles, trending, DEX pairs, token safety, yields, and sentiment. Each tool earns its place with a distinct job, and the count aligns with the breadth of a comprehensive market-data service without becoming bloated.
The surface covers core market data (prices, OHLC, trending, fear/greed), DEX trading (token_pairs, screener), safety (token_risk, token_score), yields, and gas. Minor gaps include no historical yield data, no portfolio/balance tool, and no direct order/trade execution, but for a data-and-safety API the coverage is thorough with no obvious dead ends.