anti-drift
Hierarchical coordination and drift detection with frequent checkpoints, shared memory coherence validation, role specialization enforcement, and short task cycles.
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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/anti-drift/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How anti-drift Compares
| Feature / Agent | anti-drift | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/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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