Crypto Fear & Greed Index: current and previous value plus classification (Extreme Fear to Extreme Greed), with recent history. Best used as a contrarian sentiment signal, not on its own.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | 0-100. Low is fear, high is greed. | |
| history | Yes | ||
| previousValue | No | ||
| classification | Yes | ||
| previousClassification | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the description has less burden. It adds value by explaining the qualitative classification (Extreme Fear to Extreme Greed) and that it includes recent history, which are useful behavioral traits beyond the annotations.
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 two sentences with no redundancy. The first sentence front-loads the core purpose and return values, and the second adds usage guidance. Every sentence is necessary and earns its place.
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 has zero parameters, comprehensive annotations, and an output schema (mentioned in context), the description is complete. It covers purpose, return content, and usage context without requiring additional details.
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?
With 0 parameters and 100% schema coverage, the baseline is 4. The description adds no parameter info, but none is needed. It correctly describes what the tool returns without parameter details.
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 verb 'get' and resource 'Fear & Greed Index', specifies what it returns (current and previous value, classification, recent history), and distinguishes it from sibling tools like get_market_quotes or get_market_history by focusing on sentiment rather than price or network data.
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 explicitly advises using it as a 'contrarian sentiment signal' and cautions 'not on its own', providing clear context for when to apply it. However, it does not explicitly mention when not to use it or name specific alternatives among the sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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Each tool targets a distinct data domain—network health, market prices, news, DeFi, derivatives per-venue vs aggregate, economic calendar, ETH address, whale flows, execution cost, sentiment, implied volatility, macro rates, market brief, dominance, history, and traditional market quotes. The only similar pair (get_derivatives vs get_derivatives_aggregate) is clearly differentiated by level of detail, so there is no real ambiguity.
All tools follow the get_<domain> pattern with descriptive noun phrases (e.g., get_btc_network, get_eth_whale_flows, get_market_brief). No mixed verb styles or casing conventions appear, making the naming fully predictable and consistent.
At 17 tools, the surface is slightly above the ideal 3-15 range, but the breadth of the domain—spot, derivatives, on-chain, macro, sentiment, and execution—justifies each tool. It's borderline but each tool earns its place in a comprehensive market analysis agent.
The toolset covers nearly every major facet of crypto market analysis: prices, history, dominance, derivatives, on-chain activity, DeFi, macro, economic calendar, sentiment, implied volatility, execution cost, and a composite brief. Minor gaps like historical OHLCV or multi-chain on-chain analytics are not critical given the agent's stated focus.