anti-drift

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

509 stars

Best use case

anti-drift is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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

Teams using anti-drift should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/anti-drift/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/methodologies/ruflo/skills/anti-drift/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/anti-drift/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How anti-drift Compares

Feature / Agentanti-driftStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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`

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