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:
query DailyActiveMultisigs($timestamp_gt: Int!, $timestamp_lt: Int!) {
dailyActiveMultisigs_collection(
where: {
and: [
{ dayTimestamp_gt: $timestamp_gt }
{ dayTimestamp_lt: $timestamp_lt }
]
}
orderBy: dayTimestamp
orderDirection: desc
) {
id
count
}
}
Tracks how many unique multisigs were active each day for selected agents on Mode and Optimism. This metric is useful to understand the operational footprint and engagement of specific agents over time. The active multisig count reflects the number of unique multisigs that performed at least one on-chain interaction attributed to a given agent within the UTC day window.
The following query is used to compute daily active agents:
query DailyPerformance($timestamp_gt: Int!, $timestamp_lt: Int!) {
dailyAgentPerformances(
where: {
and: [
{ agentId: 40 }
{ dayTimestamp_gt: $timestamp_gt }
{ dayTimestamp_lt: $timestamp_lt }
]
}
orderBy: dayTimestamp
orderDirection: desc
) {
id
activeMultisigCount
}
}
Tracks how many unique multisigs were active each day for selected agents on Gnosis and Base. This metric is useful to understand the operational footprint and engagement of specific agents over time. The active multisig count reflects the number of unique multisigs that performed at least one on-chain interaction attributed to a given agent within the UTC day window.
The following query is used to compute daily active agents:
query DailyPerformance($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
}
}
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:
query RegistryGlobals {
global(id: "") {
id
txCount
}
}
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:
query StakingGlobals {
global(id: "") {
totalRewards
currentOlasStaked
}
}
Total ROI shows your agent's overall earnings, including profits from predictions and staking rewards, minus all related costs such as bet amounts, gas fees, and Mech request fees. Requests made for unresolved (open) markets are excluded to ensure accuracy.
The following queries are used to define the value:
query TotalMechRequests {
global(id: "") {
totalRequests
}
}
query MechRequests {
_page1: requests(
first: 1000
skip: 0
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
_page2: requests(
first: 1000
skip: 1000
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
_page3: requests(
first: 1000
skip: 2000
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
_page4: requests(
first: 1000
skip: 3000
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
_page5: requests(
first: 1000
skip: 4000
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
_page6: requests(
first: 1000
skip: 5000
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
_page7: requests(
first: 1000
skip: 6000
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
_page8: requests(
first: 1000
skip: 7000
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
_page9: requests(
first: 1000
skip: 8000
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
_page10: requests(
first: 1000
skip: 9000
where: { blockTimestamp_gt: 1754784000 }
) {
id
questionTitle
blockTimestamp
}
}
query MarketsAndBets {
fixedProductMarketMakerCreations(
where: { blockTimestamp_gt: 1754784000 }
) {
id
question
}
global(id: "") {
totalFees
totalPayout
totalTraded
}
}
Used for getting cumulative staking rewards in OLAS
Subgraph link
query StakingGlobals {
global(id: "") {
totalRewards
currentOlasStaked
}
}
Success rate shows how often your agent's predictions were correct in resolved markets. Bets on unresolved markets or with invalid outcomes are excluded, and the rate is based on the latest 10,000 bets from closed markets to ensure performance remains relevant.
The following query is used:
Used to fetch all bets along with their outcome and the final answer of the associated market
Subgraph link
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
}
}
}