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get_fear_greed

Fear & Greed Index with history. $0.005.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
api_keyYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • removedInput schema / properties / api_key / description
      Removed value: -"Your API key"
  2. First observed

TDQS

C2.9/5.0
Behavior3/5

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

Mentions the cost ($0.005) and that history is included, providing some behavioral context. However, with no annotations, the description should disclose more about rate limits, pagination, or required authentication beyond api_key. The cost info is a positive but insufficient.

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

Conciseness3/5

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

Extremely concise and front-loaded with the core purpose. However, it sacrifices necessary detail, leaving critical gaps. Conciseness is beneficial but not when it omits required information for a tool with two undocumented parameters.

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

Completeness2/5

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

Fails to provide enough context given no output schema, no annotations, and incomplete parameter explanations. The agent cannot infer what the response includes, how limit affects results, or if there are any constraints. Incomplete for a tool with this complexity.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not explain either parameter. The 'limit' parameter's purpose and effect are unclear, and 'api_key' is mentioned only as required with no additional context. The description adds no value over the schema.

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?

Clearly states it retrieves the Fear & Greed Index with historical data. The name 'get_fear_greed' combined with the description makes the purpose unambiguous and distinct from sibling crypto tools.

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

Usage Guidelines2/5

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

No guidance on when to use this tool vs. siblings. Does not specify prerequisites, use cases, or exclusions. The agent receives no help in deciding between this and alternative 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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TDQS

C2.8/5.0
Disambiguation4/5

Tools generally have distinct purposes, but some overlap exists between price history tools (get_ohlc vs get_price_summary) and meme-related tools (analyze vs scan vs trending). Overall, descriptions help differentiate.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern (e.g., get_price, set_price_alert, analyze_contract). No mixing of conventions.

Tool Count3/5

48 tools is on the higher side, but it covers a broad spectrum of crypto data (prices, DeFi, sentiment, alerts, etc.) and each tool seems justified. However, the count could be slimmed down by grouping similar functions.

Completeness4/5

Very comprehensive coverage of crypto data: prices, market stats, DeFi, sentiment, gas, alerts, portfolio, arbitrage, token analysis. Minor gaps like NFT data or direct exchange rate queries.

Resources