Virtuals

Virtuals Schema Description and Methodology

This schema contains comprehensive datasets for tracking Virtuals Protocol fundamental data across multiple metrics categories, including AI agent activity, trading volume, fee distribution, token economics, and market data for the decentralized AI agent marketplace.

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Available Tables

Virtuals data is available in two main tables:

• ez_metrics: Main aggregated metrics for the Virtuals Protocol
• ez_metrics_by_chain: Chain-specific metrics (currently focused on Base network)

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Table Schema

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AI Agent and Activity Metrics

Table Name	Column Name	Description
ez_metrics	daily_agents	The number of AI agents active on a given day
ez_metrics	spot_dau	The number of daily active traders on Virtuals Protocol
ez_metrics	dau	Same as spot_dau (legacy naming)

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Trading and Volume Metrics

Table Name	Column Name	Description
ez_metrics	spot_volume	The total trading volume on Virtuals Protocol
ez_metrics	volume_usd	Same as spot_volume (legacy naming)
ez_metrics	volume_native	Trading volume in native token units

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Fee Structure and Revenue Metrics

Table Name	Column Name	Description
ez_metrics	spot_fees	The total amount of fees (in USD) paid by users on Virtuals Protocol
ez_metrics	fees	The sum of all taxes, 1% fee on all trades, and agent fees (in USD) paid on Virtuals Protocol
ez_metrics	service_fee_allocation	All fees paid to AI agents on Virtuals Protocol
ez_metrics	treasury_fee_allocation	Revenue allocated to the protocol’s treasury. All taxes paid on trades first go to the treasury, then post-bond are distributed across Agent Creator (30%), Agent Affiliates (20%), and Agent subDAO (50%)
ez_metrics	fee_fun_usd	Agent fees collected in USD (legacy naming)
ez_metrics	fee_fun_native	Agent fees collected in native tokens (legacy naming)
ez_metrics	tax_usd	Tax fees collected from trades (legacy naming)
ez_metrics	fees	Total fees collected (legacy naming)

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Token Supply Metrics

Table Name	Column Name	Description
ez_metrics	circulating_supply_native	The circulating supply of VIRTUALS tokens in native units
ez_metrics	net_supply_change_native	The net change in the circulating supply of VIRTUALS tokens
ez_metrics	premine_unlocks_native	The amount of native VIRTUALS tokens unlocked from premine

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Market and Token Metrics

Table Name	Column Name	Description
ez_metrics	price	The price of VIRTUALS token in USD
ez_metrics	market_cap	The market cap of VIRTUALS token in USD
ez_metrics	fdmc	The fully diluted market cap of VIRTUALS token in USD
ez_metrics	token_volume	The trading volume of VIRTUALS token in USD
ez_metrics	token_turnover_circulating	The turnover of VIRTUALS token based on circulating supply
ez_metrics	token_turnover_fdv	The turnover of VIRTUALS token based on fully diluted valuation

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Chain-Specific Metrics

Table Name	Column Name	Description
ez_metrics_by_chain	chain	The blockchain (currently ‘base’)
ez_metrics_by_chain	trading_volume	Trading volume on the specific chain
ez_metrics_by_chain	volume_native	Trading volume in native token units
ez_metrics_by_chain	ai_volume	AI-related trading volume (same as trading_volume)

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Sample Queries

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Basic Protocol Activity Query

-- Pull fundamental activity data for Virtuals Protocol
SELECT
    date,
    daily_agents,
    spot_dau,
    spot_volume,
    spot_fees,
    fees,
    price
FROM
    art_share.virtuals.ez_metrics
WHERE
    date >= DATEADD(month, -3, CURRENT_DATE())
ORDER BY
    date ASC

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AI Agent Activity Analysis

-- Analyze AI agent activity and user engagement
SELECT
    date,
    daily_agents,
    spot_dau,
    spot_volume,
    spot_volume / NULLIF(spot_dau, 0) as avg_volume_per_user,
    spot_volume / NULLIF(daily_agents, 0) as avg_volume_per_agent,
    spot_dau / NULLIF(daily_agents, 0) as avg_users_per_agent
FROM
    art_share.virtuals.ez_metrics
WHERE
    date >= DATEADD(month, -2, CURRENT_DATE())
    AND daily_agents > 0
ORDER BY
    date ASC

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Fee Distribution Analysis

-- Analyze Virtuals Protocol fee structure and distribution
SELECT
    date,
    ecosystem_