anti-drift

SkillDocs & knowledge

Lets your agent stay on task during long multi-step work by checking progress against a plan at frequent checkpoints.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the anti-drift skill

About this capability

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

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/methodologies/ruflo/skills/anti-drift/SKILL.md and read by ahel’s review.

  • 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

Signals

GitHub stars
2k
Forks
106
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
anti-drift
Source
github.com/a5c-ai/babysitter