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trending

Identify trending cryptocurrencies by analyzing current search and trading activity data to monitor market movements.

Instructions

Get trending cryptocurrencies right now — what people are searching for and trading.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The `getTrending` function fetches data from CoinGecko API to retrieve trending cryptocurrencies.
    async function getTrending() {
      const data = await fetch('https://api.coingecko.com/api/v3/search/trending');
      return {
        coins: data.coins.map(c => ({
          name: c.item.name,
          symbol: c.item.symbol,
          market_cap_rank: c.item.market_cap_rank,
          price_btc: c.item.price_btc,
        })),
      };
    }
  • index.js:282-286 (registration)
    The 'trending' tool is registered in the MCP tool definitions list.
    {
      name: 'trending',
      description: 'Get trending cryptocurrencies right now — what people are searching for and trading.',
      inputSchema: { type: 'object', properties: {} }
    },
  • The MCP handler calls `getTrending` when the 'trending' tool is requested.
    case 'trending':
      return await getTrending();
Behavior3/5

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

With no annotations provided, the description carries the full disclosure burden. It adds valuable context about data composition (search interest + trading volume) and temporality ('right now'), but omits safety classification (read-only implied but not stated), rate limits, error behaviors, or return structure.

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 single sentence is efficiently front-loaded with the core action ('Get trending cryptocurrencies right now') and uses the em-dash to append clarifying context without verbosity. Every word earns its place.

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 zero-parameter tool without output schema, the description adequately covers the essential semantic context (what 'trending' means in this domain). However, it could be improved by mentioning that it returns a list/ranking of coins to fully substitute for the missing output schema documentation.

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 contains zero parameters (empty properties), establishing a baseline of 4. The description appropriately makes no parameter claims, and with 100% schema coverage of zero fields, no additional semantic elaboration is required.

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 provides a clear verb ('Get') and resource ('trending cryptocurrencies'), and the em-dash clarification ('what people are searching for and trading') uniquely defines the resource methodology. However, it does not explicitly differentiate from siblings like 'price' or 'market_cap' by name, only by implication.

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

Usage Guidelines3/5

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

The description implies usage by defining what constitutes 'trending' (search and trading activity), suggesting when to use this versus pure price lookups. However, it lacks explicit 'when to use' or 'use X instead for Y' guidance that would make selection foolproof against siblings like 'feargreed' or 'price'.

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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