[$0.002 USDC per call via x402] Spot prices for one or more cryptocurrencies in any fiat/crypto quote currency. Comma-separated CoinGecko ids.
| Name | Required | Description | Default |
|---|---|---|---|
| vs | No | Quote currency (default usd), e.g. usd, eur, btc | |
| ids | Yes | Comma-separated CoinGecko coin ids, e.g. bitcoin,ethereum,solana |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the pricing model ($0.002 USDC per call via x402) which is useful cost context. However, it doesn't describe response format, rate limits, or whether it returns a single price or full market data blob for each id.
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 efficient—two compact sentences covering cost and function. The pricing info is front-loaded, which is useful. No wasted words, though it could be slightly more complete.
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?
For a simple 2-param tool with 100% schema coverage and no output schema, the description is largely adequate. However, it omits what the response looks like (since there's no output schema) and doesn't state any limit on number of ids or error behavior for invalid CoinGecko ids.
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 both parameters (ids, vs) are already documented in the schema. The description adds the default quote currency (usd) context, which the schema also covers. It adds marginal value by confirming the comma-separated format for ids, but this mostly mirrors the schema.
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 provides spot prices for cryptocurrencies in various quote currencies, using CoinGecko ids. It distinguishes from siblings like ohlc (history) and market_summary, though it doesn't explicitly name alternatives.
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 implies usage context (spot price lookup) but doesn't explicitly state when to use it vs siblings like market_summary or ohlc. No exclusions or alternative tool names are given, leaving the agent to infer based on purpose.
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.
