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whale-insights

whale-insights

by cryptowhaleinsights-ux
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript

fear_greed_history

Retrieve daily Fear & Greed scores (0-100) with extreme fear/greed labels for up to 180 days to analyze market sentiment trends.

Instructions

Get daily Fear & Greed score history — 0-100 score + Extreme Fear/Greed label per day over up to 180 days (use fear_greed_monthly for 2-year trends) — Daily historical Fear & Greed score and classification for the last N days (default 30, max 180). One row per day saved from the platform's 7-factor composite index. Useful for trend analysis and AI agent context. DB-backed, 5-min cache.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "fear_greed_history"
  }
}

Input Schema

NameRequiredDescriptionDefault
daysNoNumber of days of history to return (1–180, default 30).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.2

TDQS

A3.9/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry behavioral weight, and it does disclose useful traits: one row per day, source from a 7-factor composite index, DB-backed, and 5-minute cache. However, it never describes the return shape (e.g., ordering, date format) or staleness implications beyond the cache, and the 'max 180' phrase conflicts with the schema's maximum of 90.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core action and output, then adds useful context (alternative tool, use case, cache). It is slightly redundant because the first clause and the second clause both describe daily historical Fear & Greed scoring, but no sentence is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one optional parameter and no output schema, the description gives sufficient invocation context: range, labels, granularity, data source, and cache behavior. It lacks a concrete example or output ordering, but these are minor omissions rather than blockers.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage for the single days parameter is 100%, so the description adds little beyond the schema: it restates default 30 and max 180. The description also propagates the max-180 claim even though the schema's maximum constraint is 90, creating avoidable ambiguity for an agent choosing a value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Get daily Fear & Greed score history,' and immediately defines the output (0-100 score plus Extreme Fear/Greed label per day). It also names a sibling (fear_greed_monthly) for longer trends, so an agent can distinguish this tool from related history tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly recommends fear_greed_monthly for 2-year trends and states this tool is useful for trend analysis/AI agent context, giving clear use context. It does not enumerate exclusions against other siblings such as fear_greed or sentiment_history, so it falls just short of full alternative routing.

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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