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get_trending_crypto

Identify top trending cryptocurrencies within the last 24 hours to monitor market movements and inform trading decisions.

Instructions

Gets the top trending cryptocurrencies in the last 24 hours.

Returns:
    Formatted string with trending coins

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The core handler function that fetches top trending cryptocurrencies from CoinGecko API and formats them into a readable string list.
    def get_trending_crypto() -> str:
        """
        Gets the top trending cryptocurrencies in the last 24 hours.
        
        Returns:
            Formatted string with trending coins
        """
        try:
            data = cg.get_search_trending()
            coins = data.get('coins', [])
            
            if not coins:
                return "No trending coins data available"
                
            summary = ["=== TRENDING CRYPTOCURRENCIES (24h) ===\n"]
            
            for i, item in enumerate(coins[:10], 1):
                coin = item.get('item', {})
                summary.append(
                    f"{i}. {coin.get('name')} ({coin.get('symbol', 'N/A').upper()})"
                    f" - Rank #{coin.get('market_cap_rank', 'N/A')}"
                )
                
            return "\n".join(summary)
        except Exception as e:
            logger.error(f"CoinGecko error: {e}")
            return f"Error fetching trending coins: {str(e)}"
  • server.py:414-418 (registration)
    Registers get_trending_crypto as an MCP tool in the 'Cryptocurrency' category using the register_tools helper function.
    register_tools(
        [get_crypto_price, get_crypto_market_data, get_trending_crypto, search_crypto],
        "Cryptocurrency"
    )
  • app.py:295-302 (registration)
    Includes get_trending_crypto in the 'Crypto' tools group for the Gradio toolbox and MCP server in the app.py dual-mode application.
    "Crypto": [
        get_crypto_price,
        get_crypto_market_data,
        get_trending_crypto,
        search_crypto,
        get_crypto_resource,
        crypto_market_update,
    ],
  • Global CoinGeckoAPI client initialization used by get_trending_crypto and other crypto tools.
    cg = CoinGeckoAPI()
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the tool 'Gets' data and returns a 'Formatted string', but lacks details on behavioral traits such as rate limits, authentication needs, data sources, or error handling. This leaves significant gaps in understanding how the tool behaves in practice.

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?

The description is extremely concise and well-structured, consisting of two brief sentences that directly state the purpose and return value. Every word earns its place, with no wasted information, making it easy to parse quickly.

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

Completeness3/5

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

Given the tool's simplicity (0 parameters, output schema provided), the description is minimally adequate. It covers the basic purpose and return format, but with no annotations and a lack of behavioral details, it doesn't fully prepare an agent for potential complexities like data freshness or formatting specifics.

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 input schema has 0 parameters with 100% coverage, so no parameter information is needed. The description appropriately doesn't discuss parameters, which is efficient and avoids redundancy, earning a high score for not adding unnecessary details.

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

Purpose4/5

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 ('Gets') and resource ('top trending cryptocurrencies in the last 24 hours'), making it easy to understand what it does. However, it doesn't explicitly distinguish itself from potential sibling tools like 'get_crypto_market_data' or 'search_crypto', which might also provide related cryptocurrency information.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context, or exclusions, leaving the agent to infer usage based on the purpose alone without any explicit direction.

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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