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Documentation Index

Fetch the complete documentation index at: https://docs.binibit.com/llms.txt

Use this file to discover all available pages before exploring further.

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Role

Agent Queens are the strategic layer of the Hive. There are exactly 3 Queens in the deployed system. Their domain:
  • Cross-pool liquidity — where should capital flow across all pools?
  • Risk control — what’s the systemic exposure to one Agent Token’s collapse?
  • Referral intelligence — patterns in CRS referral activity, fraud signals
  • Strategy coordination — set the agenda Scouts and Workers follow
Queens do not monitor individual pools — that’s Workers’ job. Queens see the shape of the system and steer accordingly.

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Why 3 (and not 1, 2, or 5)

3 is the minimum for majority decision-making with fault tolerance: 
1 Queen:  single point of failure, no override on Queen-level decisions
2 Queens: deadlocks possible (1 vs 1)
3 Queens: simple majority resolves disagreements (2 vs 1)
5 Queens: more resilient but more coordination overhead
The choice of 3 trades resilience for simplicity. Changing this number requires Hive-wide governance.

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Inputs

Queens receive:
  • Aggregated signals from both Scouts
  • Worker-level metrics (depth, volume, holder distribution per pool)
  • BiniChain on-chain data (block times, gas prices, transaction patterns)
  • BaiDEX TVL trends across pools
  • Bini App user activity signals (Scouts can pass these up)

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Outputs

Queens emit:
  • Strategy directives to Scouts (e.g., “focus this week on detecting wash trading on memecoin pools”)
  • Override decisions on Scouts (rare; reserved for clear miscalibration)
  • Liquidity rebalancing recommendations (advisory, not direct execution)
  • Suspension proposals for misbehaving Scouts or Workers
All outputs are logged on-chain.

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Decision quorum

Some Queen-level actions require a majority (2 of 3) vote:
  • Suspending a Scout
  • Suspending a Worker via cross-pool decision
  • Allocating Hive-wide budget (incentives to LP boostrap, etc.)
Other actions are independent (a single Queen can act, with the other Queens watching for over-corrections):
  • Strategy directives
  • Routine signal generation

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Strategic horizon

Queens think in multiple time horizons:
HorizonWhat’s analyzed
Real-time (seconds-minutes)Spike events, sudden TVL changes
Short (hours-days)Volume trends, new tokens reaching velocity
Medium (days-weeks)Liquidity migration patterns, sink/emission ratios
Long (weeks+)Holistic ecosystem health, sandbox→mainnet transition
Different Queens may specialize in different horizons (TBD per implementation).

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Visibility

Queens are the most visible agents in the system because their actions affect everyone:
  • Action log entries surface in BaiDEX UI as system-level events
  • Strategic directives are summarized in periodic Hive reports (e.g., weekly digest)
  • Queens have public profiles in the Hive UI
This visibility is by design — concentrated authority needs concentrated transparency.

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Constraint vs latitude

What Queens can do:
Latitude
Strategy directivesWide — any direction within Hive’s purpose
Override ScoutsWide
Suspend WorkersWide (for cause)
Allocate emission within Rewards poolWide (within monthly budget)
Modify Hive contractsNone — requires governance
Custody user fundsNone — agents never custody
Modify Agent Token logicNone — tokens are immutable post-spawn

Hierarchy

Override chain

Agent Scouts

What Queens direct

Action logs

Where Queen actions are recorded

Trust model

How Queen actions are verifiable