fear_greed
[$0.002 USDC per call via x402] Current Crypto Fear & Greed Index value and classification, plus previous day for trend.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
[$0.002 USDC per call via x402] Current Crypto Fear & Greed Index value and classification, plus previous day for trend.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses pricing ($0.002 USDC per call via x402) which is genuinely useful operational context beyond the schema. However, it doesn't describe return format, error cases, or rate behavior — but for a zero-parameter read-only sentiment tool this is reasonably adequate.
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?
One compact sentence conveys pricing, the resource, the value type (index + classification), and the additional previous-day trend data. It's front-loaded with the most important scoping information first. Slightly under-specified on what the 'classification' values might be (e.g., 'Extreme Fear', 'Greed'), but no explicit waste.
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 zero-parameter, no-output-schema read tool, the description is nearly complete. It states the data returned (value, classification, previous day for trend) which covers the practical return contract. It could mention the classification scale band, but that's a minor gap for a simple sentiment endpoint.
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, and schema coverage is 100% (trivially so, since there are no parameters to document). The description fully covers what the tool returns. There's nothing more parameter semantics could add since no parameters exist.
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 the current Crypto Fear & Greed Index value, classification, and previous day for trend. The verb 'Current... value and classification' with the specific resource (Fear & Greed Index) is distinct from siblings like gas, price, and market_summary which cover different data domains.
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 vs alternatives, but the domain (Crypto Fear & Greed Index) is highly specific and distinct from all siblings (gas, price, screener, yields, etc.), making the use case self-evident. The 'previous day for trend' hint clarifies this is for sentiment/market-mood context rather than price data.
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.