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get_overall_market_stats

Retrieve comprehensive Axie Infinity marketplace statistics including new Axies minted, trading volumes in RON and USD, total transactions, and ascended Axies data.

Instructions

Get overall marketplace statistics including new Axies minted, marketplace volumes in RON and USD, total transactions, and ascended Axies.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler logic for the 'get_overall_market_stats' tool, which executes a GraphQL query and returns the market stats.
    case "get_overall_market_stats": {
      const data = await client.query<{ overallMarketStats: unknown }>(
        queries.GET_OVERALL_MARKET_STATS
      );
      return jsonContent(data.overallMarketStats);
    }
  • src/index.ts:253-262 (registration)
    Registration of the 'get_overall_market_stats' tool with its schema and description.
    {
      name: "get_overall_market_stats",
      description:
        "Get overall marketplace statistics including new Axies minted, marketplace volumes in RON and USD, total transactions, and ascended Axies.",
      inputSchema: {
        type: "object",
        properties: {},
        required: [],
      },
    },
  • The GraphQL query definition for 'get_overall_market_stats'.
    export const GET_OVERALL_MARKET_STATS = `
      query GetOverallMarketStats {
        overallMarketStats {
          newAxies { last24H last7D last30D allTime }
          mkpVolume { last24H last7D last30D allTime }
          mkpTxs { last24H last7D last30D allTime }
          mkpVolumeInUsdAllTime
          ascendedAxiesLast7D
        }
      }
    `;
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. While it clearly describes what data is returned, it doesn't address important behavioral aspects like whether this is a real-time or cached data source, rate limits, authentication requirements, or potential data freshness issues. For a data retrieval tool with zero annotation coverage, this represents a significant gap in behavioral transparency.

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 that packs substantial information. It front-loads the core purpose ('Get overall marketplace statistics') and then provides specific examples of what's included. There's zero wasted language or redundancy, making it maximally concise while still informative.

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?

For a parameterless tool with no output schema, the description provides adequate information about what data is returned. However, without annotations covering behavioral aspects and with sibling tools that might overlap in functionality, the description doesn't provide complete context for optimal tool selection and usage. It tells what you get but not important contextual details about data freshness, limitations, or differentiation from similar tools.

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 description coverage, so the baseline score would be 3. However, the description appropriately acknowledges this by not attempting to describe non-existent parameters while clearly indicating what data will be returned. The description adds value by specifying the types of statistics included, which helps the agent understand what to expect from this parameterless query.

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: 'Get overall marketplace statistics' with specific examples of what statistics are included (new Axies minted, marketplace volumes in RON and USD, total transactions, and ascended Axies). It distinguishes itself from sibling tools like 'get_market_stats' by specifying 'overall' statistics rather than more granular market data. However, it doesn't explicitly contrast with 'get_market_stats' in the description text itself.

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. With sibling tools like 'get_market_stats' and 'get_top_sales' that might provide overlapping or related market data, there's no indication of when this 'overall' statistics tool is appropriate versus more specific market tools. The description simply states what the tool does without contextual usage information.

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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