anti-drift

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Hierarchical coordination and drift detection with frequent checkpoints, shared memory coherence validation, role specialization enforcement, and short task cycles.

AI & Automation 814 stars 53 forks Updated today MIT

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# Anti-Drift ## Overview Prevent agent swarms from drifting away from the original task goal through hierarchical coordination, frequent checkpoints, and shared memory validation. ## When to Use - Long-running multi-agent orchestrations - Tasks with high risk of scope creep - When multiple agents work on related subtasks - Critical tasks where deviation is costly ## Anti-Drift Mechanisms 1. **Hierarchical Coordinator** - Queen agent validates alignment at checkpoints 2. **Frequent Checkpoints** - Every 2 subtasks (configurable) 3. **Shared Memory Coherence** - Validate all agents see consistent state 4. **Short Task Cycles** - Bounded execution windows prevent runaway agents 5. **Role Specialization** - Agents stay within their assigned scope ## Drift Scoring - `0.0-0.1`: Fully aligned, no intervention needed - `0.1-0.3`: Minor drift, automatic correction - `0.3-0.5`: Significant drift, checkpoint correction with logging - `0.5+`: Critical drift, human escalation via breakpoint ## Agents Used - `agents/swarm-coordinator/` - Drift detection and correction - `agents/tactical-queen/` - Checkpoint enforcement - `agents/adaptive-queen/` - Real-time course correction ## Tool Use Invoke via babysitter process: `methodologies/ruflo/ruflo-swarm-coordination`

Details

Author
a5c-ai
Repository
a5c-ai/babysitter
Created
4 months ago
Last Updated
today
Language
JavaScript
License
MIT

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