Data verification

Tracks how many unique multisigs were active each day for all agents across all supported networks. This metric is useful to understand the operational footprint and engagement of specific agents over time. The active multisig count reflects the number of unique multisigs that performed at least one on-chain interaction attributed to a given agent within the UTC day window.

The following query is used to compute daily active agents:

Daily Active Multisigs query

Subgraph links: EthereumGnosisBaseModeOptimismCeloArbitrumPolygon

Copy
  query DailyActiveMultisigs($timestamp_gt: Int!, $timestamp_lt: Int!) {
    dailyActiveMultisigs_collection(
      where: { and: [{ dayTimestamp_gt: $timestamp_gt }, { dayTimestamp_lt: $timestamp_lt }] }
      orderBy: dayTimestamp
      orderDirection: desc
    ) {
      id
      count
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks how many unique multisigs were active each day for Babydegen agents. This metric is useful to understand the operational footprint and engagement of specific agents over time. The active multisig count reflects the number of unique multisigs that performed at least one on-chain interaction attributed to a given agent within the UTC day window.

The following query is used to compute daily active agents:

Daily Performance query

Subgraph links: ModeOptimism

Copy
  query DailyPerformance($timestamp_gt: Int!, $timestamp_lt: Int!) {
    dailyAgentPerformances(
      where: {
        and: [
          { agentId: 40 }
          { dayTimestamp_gt: $timestamp_gt }
          { dayTimestamp_lt: $timestamp_lt }
        ]
      }
      orderBy: dayTimestamp
      orderDirection: desc
    ) {
      id
      dayTimestamp
      activeMultisigCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks how many unique multisigs were active each day for Agents.fun agents. The active multisig count reflects the number of unique multisigs that performed at least one on-chain interaction attributed to a given agent within the UTC day window.

The following query is used to compute daily active agents:

Daily Performance query

Subgraph links: Base

Copy
  query DailyPerformance($timestamp_gt: Int!, $timestamp_lt: Int!) {
    dailyAgentPerformances(
      where: {
        and: [
          { agentId: 43 }
          { dayTimestamp_gt: $timestamp_gt }
          { dayTimestamp_lt: $timestamp_lt }
        ]
      }
      orderBy: dayTimestamp
      orderDirection: desc
    ) {
      id
      dayTimestamp
      activeMultisigCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks how many unique multisigs of Mech agents were active each day. This metric is useful to understand the operational footprint and engagement of specific agents over time. The active multisig count reflects the number of unique multisigs that performed at least one on-chain interaction attributed to a given agent within the UTC day window.

The following query is used to compute daily active agents:

Daily Performance query

Subgraph links: GnosisBaseOptimismPolygon

Copy
  query DailyPerformance($timestamp_gt: Int!, $timestamp_lt: Int!) {
    dailyAgentPerformances(
      where: {
        and: [
          {
            or: [{ agentId: 9 }, { agentId: 26 }, { agentId: 29 }, { agentId: 36 }, { agentId: 37 }]
          }
          { dayTimestamp_gt: $timestamp_gt }
          { dayTimestamp_lt: $timestamp_lt }
        ]
      }
      orderBy: dayTimestamp
      orderDirection: desc
    ) {
      id
      activeMultisigCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks unique multisigs active each day for Omenstrat agents on Gnosis chain. Omenstrat agents participate in Omen prediction markets. The active multisig count reflects multisigs that performed at least one on-chain interaction within the UTC day window.

Daily Performance query

Subgraph link: Gnosis

Note: this query uses the following agentId_in parameter: [14, 25]

Copy
  query DailyPredictPerformances($agentIds: [Int!]!, $timestamp_gt: Int!, $timestamp_lt: Int!) {
    dailyAgentPerformances(
      where: {
        and: [
          { agentId_in: $agentIds }
          { dayTimestamp_gt: $timestamp_gt }
          { dayTimestamp_lt: $timestamp_lt }
        ]
      }
      orderBy: dayTimestamp
      orderDirection: asc
      first: 1000
    ) {
      dayTimestamp
      activeMultisigCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks unique multisigs active each day for Polystrat agents on Polygon chain. Polystrat agents participate in Polymarket. The active multisig count reflects multisigs that performed at least one on-chain interaction within the UTC day window.

Daily Performance query

Subgraph link: Polygon

Note: This query uses the following agentId_in parameter: [86]

Copy
  query DailyPredictPerformances($agentIds: [Int!]!, $timestamp_gt: Int!, $timestamp_lt: Int!) {
    dailyAgentPerformances(
      where: {
        and: [
          { agentId_in: $agentIds }
          { dayTimestamp_gt: $timestamp_gt }
          { dayTimestamp_lt: $timestamp_lt }
        ]
      }
      orderBy: dayTimestamp
      orderDirection: asc
      first: 1000
    ) {
      dayTimestamp
      activeMultisigCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks how many unique multisigs were active each day for all agents in the Pearl app. The active multisig count reflects the number of unique multisigs that performed at least one on-chain interaction attributed to these agents within the UTC day window.

The following queries are used to compute Pearl daily active agents:

Pearl Prediction Agents Query

Subgraph links: Gnosis

Copy
  query DailyPredictPerformances($agentIds: [Int!]!, $timestamp_gt: Int!, $timestamp_lt: Int!) {
    dailyAgentPerformances(
      where: {
        and: [
          { agentId_in: $agentIds }
          { dayTimestamp_gt: $timestamp_gt }
          { dayTimestamp_lt: $timestamp_lt }
        ]
      }
      orderBy: dayTimestamp
      orderDirection: asc
      first: 1000
    ) {
      dayTimestamp
      activeMultisigCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Optimus Babydegen Query

Subgraph links: Optimism

Copy
  query DailyPerformance($timestamp_gt: Int!, $timestamp_lt: Int!) {
    dailyAgentPerformances(
      where: {
        and: [
          { agentId: 40 }
          { dayTimestamp_gt: $timestamp_gt }
          { dayTimestamp_lt: $timestamp_lt }
        ]
      }
      orderBy: dayTimestamp
      orderDirection: desc
    ) {
      id
      dayTimestamp
      activeMultisigCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks how many unique agent-41 services received ETH each day on Base. The count reflects the number of unique services that were active within the UTC day window.

The following query is used to compute daily active agents:

Daily Activities Query

Subgraph links: Base

Copy
  query DailyActivities(
    $first: Int
    $where: DailyActivity_filter
    $orderBy: DailyActivity_orderBy
    $orderDirection: OrderDirection
  ) {
    dailyActivities(
      first: $first
      where: $where
      orderBy: $orderBy
      orderDirection: $orderDirection
    ) {
      id
      dayTimestamp
      count
      services
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

This API aggregates BabyDegen agent metrics from the BabyDegen and staking subgraphs. Population metrics (daily APR projections, agent age, and funded AUM) are fetched from the BabyDegen subgraph, while staking reward snapshots come from the staking subgraphs. Together with the live OLAS price, those datasets are used to compute the derived APR exposed on the BabyDegen economy page.

The resulting API response populates the Optimus agent economy card with three values:

• APR, Relative to USDC - Moving Average 7D maps to the sma7dProjectedUnrealisedPnL field from the population metrics query.
• APR, Relative to ETH - Moving Average 7D maps to the sma7dEthAdjustedProjectedUnrealisedPnL field in the same response.
• APR, OLAS - Via OLAS Staking is derived by combining the population metrics with staking deltas from the Optimism staking subgraph and the CoinGecko OLAS/USD price feed, following the methodology in fetch-babydegen-staking-apr.js.

BabyDegen Population Metrics Query

Subgraph link: Optimism BabyDegen

Copy
    {
      dailyPopulationMetrics(
        first: 10
        orderBy: timestamp
        orderDirection: desc
        
      ) {
        timestamp
        totalFundedAUM
        medianUnrealisedPnL
        averageAgentDaysActive
        sma7dProjectedUnrealisedPnL
        sma7dEthAdjustedProjectedUnrealisedPnL
        medianAUM
      }
      _meta {
        hasIndexingErrors
        block {
          number
        }
      }
    }
  

Optimism Staking Snapshots Query

Subgraph link: Optimism Staking

Copy
    {
      cumulativeDailyStakingGlobals(
        first: 10
        orderBy: timestamp
        orderDirection: desc
        
      ) {
        timestamp
        medianCumulativeRewards
        numServices
      }
      _meta {
        hasIndexingErrors
        block {
          number
        }
      }
    }
  

Modius Population Metrics Query

Subgraph link: Mode BabyDegen

Copy
    {
      dailyPopulationMetrics(
        first: 7
        orderBy: timestamp
        orderDirection: desc
        where: { timestamp_lte: 1758153600 }
      ) {
        timestamp
        totalFundedAUM
        medianUnrealisedPnL
        averageAgentDaysActive
        sma7dProjectedUnrealisedPnL
        sma7dEthAdjustedProjectedUnrealisedPnL
        medianAUM
      }
      _meta {
        hasIndexingErrors
        block {
          number
        }
      }
    }
  

Modius Staking Snapshots Query

Subgraph link: Mode Staking

Copy
    {
      cumulativeDailyStakingGlobals(
        first: 7
        orderBy: timestamp
        orderDirection: desc
        where: { timestamp_lte: 1758153600 }
      ) {
        timestamp
        medianCumulativeRewards
        numServices
      }
      _meta {
        hasIndexingErrors
        block {
          number
        }
      }
    }
  

Total requests and deliveries are aggregated from Mech Marketplace subgraphs on Gnosis and Base.

Mech Marketplace Globals Query

Subgraph links: Gnosis MarketplaceBase Marketplace

Copy
  query MechMarketplaceTotalRequests {
    global(id: "") {
      totalRequests
      totalDeliveries
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Predict, Contribute, and Governatooorr request counts are computed by summing per-agent totals across subgraphs using fixed agent IDs: Predict [14, 25, 13, 86], Contribute [6], Governatooorr [5]. The "Other" bucket is computed as Total Requests minus these known categories.

The query returns requestsPerAgents (marketplace requests) and requestsPerAgentOnchains (legact mech requests). The requestsCounts from both are summed together for the final totals.

Mech Marketplace Requests (per agent)

Subgraph links: GnosisBase

Copy
  query MechMarketplaceRequestsPerAgents {
    requestsPerAgents(where: { id_in: ["14", "25", "13", "86", "6", "5"] }) {
      id
      requestsCount
    }
    requestsPerAgentOnchains(where: { id_in: ["14", "25", "13", "86", "6", "5"] }) {
      id
      requestsCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Aggregates the number of unique OLAS token holders across supported networks. Each network's tokenomics subgraph is queried for the token holder count, and results are summed to obtain the total holders metric shown on the OLAS Token page.

Subgraph links: EthereumArbitrumBaseCeloGnosisOptimismPolygonMode

Copy
  query HolderCounts($tokenId: ID!) {
    token(id: $tokenId) {
      holderCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Counts the number of wallets with an active veOLAS lock on Ethereum. The metric sums all veOLAS depositors where unlockTimestamp is in the future, using the tokenomics subgraph.

The following queries power the veOLAS metrics shown on the Govern page:

Copy
  query ActiveVeOlasDepositors {
    
          _page1: veolasDepositors(
            first: 1000
            skip: 0
            where: { unlockTimestamp_gt: $unlockAfter }
            orderBy: unlockTimestamp
            orderDirection: asc
          ) {
            id
            unlockTimestamp
          }
        

          _page2: veolasDepositors(
            first: 1000
            skip: 1000
            where: { unlockTimestamp_gt: $unlockAfter }
            orderBy: unlockTimestamp
            orderDirection: asc
          ) {
            id
            unlockTimestamp
          }
        

          _page3: veolasDepositors(
            first: 1000
            skip: 2000
            where: { unlockTimestamp_gt: $unlockAfter }
            orderBy: unlockTimestamp
            orderDirection: asc
          ) {
            id
            unlockTimestamp
          }
        

          _page4: veolasDepositors(
            first: 1000
            skip: 3000
            where: { unlockTimestamp_gt: $unlockAfter }
            orderBy: unlockTimestamp
            orderDirection: asc
          ) {
            id
            unlockTimestamp
          }
        

          _page5: veolasDepositors(
            first: 1000
            skip: 4000
            where: { unlockTimestamp_gt: $unlockAfter }
            orderBy: unlockTimestamp
            orderDirection: asc
          ) {
            id
            unlockTimestamp
          }
        
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Copy
  query VeOlasLockedBalance($tokenId: ID!) {
    token(id: $tokenId) {
      balance
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks the total number of unique operators across all supported networks. This metric aggregates operator data from multiple blockchain sources to provide a comprehensive view of the autonomous agent operator ecosystem and network participation.

The following query aggregates operators from all chains:

Operators Query

Subgraph links: EthereumGnosisBaseModeOptimismCeloArbitrumPolygon

Copy
  query OperatorGlobals {
    global(id: "") {
      id
      totalOperators
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks the total number of unique builders who have developed on the Olas Stack. This metric represents developers who have created and deployed services or agents on the Olas protocol.

The following query is used to fetch the total builders:

Total Builders Query

Copy
  query TotalBuilders {
    global(id: "") {
      totalBuilders
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks the total number of transactions executed by all agents across all supported networks. This metric provides insight into the overall activity level and transaction volume generated by the autonomous agent ecosystem.

The following query is used to compute total daily transactions:

Registry Globals query

Subgraph links: EthereumGnosisBaseModeOptimismCeloArbitrumPolygon

Copy
  query RegistryGlobals {
    global(id: "") {
      id
      txCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Breaks down total Predict transactions by agent category using agent-level counters. Categories mirror the UI: Traders, Mechs (Prediction Brokers), and Market Creators/Closers.

Classification used

The following query is used to fetch per-agent tx counts:

Agent Performances query

Subgraph link: Gnosis

Copy
  query AgentTxs($agentIds: [Int!]!) {
    agentPerformances(where: { id_in: $agentIds }, orderBy: id, orderDirection: asc) {
      id
      txCount
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks agent-to-agent transactions across Gnosis, Base and Polygon networks from multiple subgraph sources. This metric aggregates transaction data from Mech Marketplace and Legacy Mech subgraphs to provide a comprehensive view of autonomous agent interaction volume and cross-chain activity.

The following query aggregates ATA transactions from all sources:

ATA Transactions Query

Subgraph links: Gnosis MarketplaceBase Marketplace

Copy
  query AtaTransactions {
    global(id: "") {
      id
      totalAtaTransactions
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks the total fees collected from the Mech Marketplace across three different sources: new mech fees from Gnosis and Base networks, and legacy mech fees from Gnosis. New mech fees are already in USD, while legacy fees are converted from wei to XDAI (treated as 1 USD equivalent) before being summed together to provide the total mech marketplace turnover.

The following queries aggregate mech fees from all three sources:

New Mech Marketplace Fees Query

Subgraph links: GnosisBase

Copy
  query NewMechFees {
    global(id: "") {
      id
      totalFeesInUSD
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Legacy Mech Fees Query

Subgraph link: Gnosis

Note: Legacy mech fees are returned in wei and converted to XDAI by dividing by 10^18 before being added to the total turnover.

Copy
  query LegacyMechFees {
    global(id: "") {
      id
      totalFeesIn
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Totals (In/Out) Queries Used by Mech fees

These include both in and out totals to compute claimed and unclaimed amounts in the API aggregator.

New Mech Fees Totals

Subgraph links: GnosisBase

Copy
  query NewMechFeesTotals {
    global(id: "") {
      totalFeesInUSD
      totalFeesOutUSD
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Legacy Mech Fees Totals

Subgraph link: Gnosis

Copy
  query LegacyMechFeesTotals {
    global(id: "") {
      totalFeesIn
      totalFeesOut
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks the total amount of OLAS tokens currently staked across all agents in the ecosystem. This metric provides insight into the overall economic security and commitment level across all supported networks.

The following query is used to compute total OLAS staked:

Staking Globals query

Subgraph links: GnosisOptimismBaseModePolygon

Copy
  query StakingGlobals {
    global(id: "") {
      totalRewards
      currentOlasStaked
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Total ROI shows your agent's overall earnings, including profits from predictions and staking rewards, minus all related costs such as trade amounts, gas fees, and Mech request fees. Requests made for unresolved (open) markets are excluded to ensure accuracy.

• Partial ROI: profit from prediction markets only.
• Final ROI: includes staking rewards (OLAS converted to USD).

The following queries are used to define the value:

1) Mech Requests query

Copy
  query TotalMechRequests {
    global(id: "") {
      totalRequests
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }
 
  query MechRequests {
    
          _page1: requests(
            first: 1000
            skip: 0
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        

          _page2: requests(
            first: 1000
            skip: 1000
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        

          _page3: requests(
            first: 1000
            skip: 2000
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        

          _page4: requests(
            first: 1000
            skip: 3000
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        

          _page5: requests(
            first: 1000
            skip: 4000
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        

          _page6: requests(
            first: 1000
            skip: 5000
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        

          _page7: requests(
            first: 1000
            skip: 6000
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        

          _page8: requests(
            first: 1000
            skip: 7000
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        

          _page9: requests(
            first: 1000
            skip: 8000
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        

          _page10: requests(
            first: 1000
            skip: 9000
            where: { blockTimestamp_gt: 1770854400 }
          ) {
            id
            blockTimestamp
            parsedRequest {
              questionTitle
            }
          }
        
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

2) Markets & Trades Query

API endpoint:https://api.subgraph.staging.autonolas.tech/api/proxy/predict-omen

Example curl request:

Copycurl -X POST https://api.subgraph.staging.autonolas.tech/api/proxy/predict-omen \
  -H "Content-Type: application/json" \
  -d '{"query":"\n  query MarketsAndBets {\n    fixedProductMarketMakerCreations(\n      where: { blockTimestamp_gt: 1770854400 }\n    ) {\n      id\n      question\n    }\n\n    global(id: \"\") {\n      totalFeesSettled\n      totalPayout\n      totalTradedSettled\n    }\n    _meta {\n      hasIndexingErrors\n      block {\n        number\n      }\n    }\n  }\n"}'

GraphQL query:

Copy
  query MarketsAndBets {
    fixedProductMarketMakerCreations(
      where: { blockTimestamp_gt: 1770854400 }
    ) {
      id
      question
    }

    global(id: "") {
      totalFeesSettled
      totalPayout
      totalTradedSettled
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

3) Staking Globals query

Used for getting cumulative staking rewards in OLAS

Copy
  query StakingGlobals {
    global(id: "") {
      totalRewards
      currentOlasStaked
    }
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

APR is computed from the OLAS staking contracts on Gnosis by querying rewards per second, minimum staking deposit, and number of agent instances, then taking the maximum APR across contracts.

Subgraph used:

Query:

Copy
  {
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
    stakingContracts(where: {instance_in: ["0xeF44Fb0842DDeF59D37f85D61A1eF492bbA6135d","0x389B46c259631Acd6a69Bde8B6cEe218230bAE8C","0x5344B7DD311e5d3DdDd46A4f71481bD7b05AAA3e","0xb964e44c126410df341ae04B13aB10A985fE3513","0x80faD33Cadb5F53f9D29F02Db97D682E8b101618","0x1c2F82413666d2a3fD8bC337b0268e62dDF67434","0x238EB6993b90a978ec6AAD7530d6429c949C08DA","0xDaF34eC46298b53a3d24CBCb431E84eBd23927dA","0x998dEFafD094817EF329f6dc79c703f1CF18bC90","0xaD9d891134443B443D7F30013c7e14Fe27F2E029","0xE56dF1E563De1B10715cB313D514af350D207212","0xBd59Ff0522aA773cB6074ce83cD1e4a05A457bc1","0x3052451e1eAee78e62E169AfdF6288F8791F2918","0x4Abe376Fda28c2F43b84884E5f822eA775DeA9F4","0x2546214aEE7eEa4bEE7689C81231017CA231Dc93","0xD7A3C8b975f71030135f1a66e9e23164d54fF455","0xdB9E2713c3dA3C403F2eA6E570eB978b00304e9E","0x1E90522b45c771DCF5f79645B9e96551d2ECaF62","0x6c65430515c70a3f5E62107CC301685B7D46f991","0x88eB38FF79fBa8C19943C0e5Acfa67D5876AdCC1","0x356C108D49C5eebd21c84c04E9162de41933030c","0x17dBAe44BC5618Cc254055b386A29576b4F87015","0xB0ef657b8302bd2c74B6E6D9B2b4b39145b19c6f","0x3112c1613eAC3dBAE3D4E38CeF023eb9E2C91CF7","0xF4a75F476801B3fBB2e7093aCDcc3576593Cc1fc","0x6C6D01e8eA8f806eF0c22F0ef7ed81D868C1aB39","0x1430107A785C3A36a0C1FC0ee09B9631e2E72aFf","0x041e679d04Fc0D4f75Eb937Dea729Df09a58e454","0x9d6e7aB0B5B48aE5c146936147C639fEf4575231","0x9fb17E549FefcCA630dd92Ea143703CeE4Ea4340","0xCAbD0C941E54147D40644CF7DA7e36d70DF46f44","0xAb10188207Ea030555f53C8A84339A92f473aa5e","0x8d7bE092d154b01d404f1aCCFA22Cef98C613B5D","0x9D00A0551F20979080d3762005C9B74D7Aa77b85","0xE2f80659dB1069f3B6a08af1A62064190c119543","0x75EECA6207be98cAc3fDE8a20eCd7B01e50b3472","0x9c7F6103e3a72E4d1805b9C683Ea5B370Ec1a99f","0xcdC603e0Ee55Aae92519f9770f214b2Be4967f7d","0x22D6cd3d587D8391C3aAE83a783f26c67ab54A85","0xaaEcdf4d0CBd6Ca0622892Ac6044472f3912A5f3","0x168aED532a0CD8868c22Fc77937Af78b363652B1"]}) {
      id
      rewardsPerSecond
      minStakingDeposit
      numAgentInstances
    }
  }

Success rate shows how often your agent's predictions were correct in resolved markets. Trades on unresolved markets or with invalid outcomes are excluded, and the rate is based on the latest 10,000 trades from closed markets to ensure performance remains relevant.

The following query is used:

Closed Markets Bets query

Used to fetch all bets along with their outcome and the final answer of the associated market

API endpoint: https://api.subgraph.staging.autonolas.tech/api/proxy/predict-omen

Example curl request:

Copycurl -X POST https://api.subgraph.staging.autonolas.tech/api/proxy/predict-omen \
  -H "Content-Type: application/json" \
  -d '{"query": "{ bets(first: 5, where: { fixedProductMarketMaker_: { currentAnswer_not: null } }) { outcomeIndex } }"}'

GraphQL query:

Copy
  query ClosedMarketsBets {
    
          _page1: bets(
            first: 1000
            skip: 0
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        

          _page2: bets(
            first: 1000
            skip: 1000
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        

          _page3: bets(
            first: 1000
            skip: 2000
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        

          _page4: bets(
            first: 1000
            skip: 3000
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        

          _page5: bets(
            first: 1000
            skip: 4000
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        

          _page6: bets(
            first: 1000
            skip: 5000
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        

          _page7: bets(
            first: 1000
            skip: 6000
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        

          _page8: bets(
            first: 1000
            skip: 7000
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        

          _page9: bets(
            first: 1000
            skip: 8000
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        

          _page10: bets(
            first: 1000
            skip: 9000
            where: { fixedProductMarketMaker_: { currentAnswer_not: null } }
            orderBy: timestamp
            orderDirection: desc
          ) {
            outcomeIndex
            fixedProductMarketMaker {
              id
              currentAnswer
            }
          }
        
    _meta {
      hasIndexingErrors
      block {
        number
      }
    }
  }

Tracks the amount of protocol fees collected and their conversion into OLAS for burning. Currently, protocol fees are set to 0% , which means no fees are generated, no tokens are converted into OLAS, and therefore no OLAS are burned at this time.

Verify on-chain: