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Multi-MCPs

by TaylorChen

get_trending_coins

Retrieve trending cryptocurrency data from CoinGecko to monitor market movements and identify popular assets for investment analysis.

Instructions

Get trending coins on CoinGecko

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'get_trending_coins' tool, which delegates to the client's getTrending method.
    async get_trending_coins() {
      return client.getTrending();
    },
  • Registration of the 'get_trending_coins' tool including name, description, and input schema.
    {
      name: "get_trending_coins",
      description: "Get trending coins on CoinGecko",
      inputSchema: { type: "object", properties: {} },
    },
  • Input schema for the 'get_trending_coins' tool, which requires no parameters.
    inputSchema: { type: "object", properties: {} },
  • Helper method in CoinGeckoClient that fetches trending coins from the CoinGecko API.
    getTrending() {
      return this.request(`/search/trending`);
    }
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 of behavioral disclosure. It states the action but doesn't add any context about what 'trending' means, how the data is sourced, rate limits, authentication needs, or response format. This leaves significant gaps in understanding the tool's behavior.

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 a single, efficient sentence with zero waste—it directly states the tool's purpose without unnecessary words. It's front-loaded and appropriately sized for a simple tool, earning full marks for conciseness.

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, no output schema, no annotations), the description is minimally adequate. However, it lacks details on what 'trending' entails and the response structure, which could help the agent use it more effectively. It's complete enough for basic use but has room for improvement.

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 documentation is needed. The description doesn't add parameter details, which is appropriate, but it also doesn't compensate for any gaps since there are none. A baseline of 4 is given as it meets the requirement for a parameterless tool.

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 action ('Get') and resource ('trending coins on CoinGecko'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_coin_price' or 'get_market_data', which are related but distinct CoinGecko operations, so it misses full sibling differentiation.

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 context, prerequisites, or exclusions, leaving the agent to infer usage from the tool name alone, which is insufficient for optimal selection.

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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