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VENTURE-AI-LABS

CryptoDataAPI MCP Server

by VENTURE-AI-LABS
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

get_market_health

Assess cryptocurrency market conditions using a dual-score system that measures long-term trend strength and short-term momentum to determine market regime and sentiment for trading decisions.

Instructions

Get the market health summary — a dual-score system (0-100) measuring long-term trend strength and short-term momentum. Returns total_score, long_term_score, short_term_score, sentiment (bullish/bearish/neutral), and market state (bear_market, early_recovery, early_bull, confirmed_bull, topping_out). Use this to quickly assess the overall market regime before making trading decisions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/tools/market-health.ts:15-17 (handler)
    The handler for the get_market_health tool, which calls the market-health summary API.
    export async function handler(_args: z.infer<typeof schema>) {
  return apiGet("/api/v1/market-health/summary");
}
  • src/tools/market-health.ts:13-13 (schema)
    The schema for get_market_health, which accepts no arguments.
    export const schema = z.object({});
  • src/index.ts:35-35 (registration)
    Registration of the marketHealth tool in the server tools list.
    marketHealth,

Tool Definition Quality

A4.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does well by explaining the scoring system (0-100 dual-score), return values (total_score, long_term_score, etc.), and the tool's purpose for market regime assessment. It doesn't mention rate limits or authentication needs, but provides substantial behavioral context.

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

Conciseness5/5

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

Two sentences with zero waste: the first explains what the tool returns, the second provides usage guidance. Every element adds value without redundancy.

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?

Given no annotations, no output schema, and 0 parameters, the description is quite complete—it explains the scoring system, return values, and usage context. It could slightly improve by mentioning the data source or update frequency, but covers the essentials well.

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

Parameters4/5

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

The tool has 0 parameters with 100% schema coverage, so the baseline is 4. The description appropriately doesn't discuss parameters, focusing instead on what the tool returns and when to use it.

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 clearly states the tool's purpose with a specific verb ('Get') and resource ('market health summary'), and distinguishes it from siblings by explaining it provides a dual-score system for overall market assessment rather than specific metrics like ETF flows or fear/greed indices.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool: 'to quickly assess the overall market regime before making trading decisions.' This provides clear context for its application versus alternatives that might offer more granular data.

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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