A comprehensive three-layer defense system to prevent AI personality drift, technical faults, and soul misalignment in autonomous agents.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install agent-stability-framework
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install agent-stability-framework using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Agent Stability Framework (ASF)?
The Agent Stability Framework (ASF) is a specialized set of Openclaw Skills designed to solve the common problem of AI reliability over long sessions. As agents interact, they often drift toward generic defaults or start hallucinating. This framework provides a structured methodology to anchor an agent's identity and ensure output consistency.
By implementing this framework, developers can ensure their agents remain on-character and technically sound. It integrates standing orders, pre-send gates, and a robust logging system to catch errors before they reach the user, making it one of the most vital Openclaw Skills for production-grade AI deployments.
Agent Stability Framework (ASF) Use Cases
- Personal AI assistants requiring a consistent, long-term persona.
- Trading and finance bots where data hallucination is a critical risk.
- Customer service agents needing to maintain a specific tone and brand voice.
- Research assistants that must adhere to strict factual accuracy and source tracking.
- Long-running autonomous agents operating 24/7 across multiple LLM sessions.
How Agent Stability Framework (ASF) Works
- Define the core identity and persona by populating the SOUL.md file.
- Establish a North Star for the agent by providing 10+ high-quality response examples in BASELINE_EXAMPLES.md.
- Apply a three-layer defense system encompassing Drift Prevention, Fault Catching, and Soul Alignment.
- Use the pre-send gate to audit responses against standing orders before they are finalized.
- Conduct periodic audits using the stability log to track performance and refine rules over time.
Agent Stability Framework (ASF) Setup
To integrate these Openclaw Skills into your project, follow these steps:
- Copy the framework files to your agent's workspace:
cp -r ./asf-templates/* ./your-agent-workspace/
- Configure the SOUL.md file to define your agent's identity.
- Populate BASELINE_EXAMPLES.md with successful interaction patterns.
- Update your agent's system prompt with the provided standing orders and pre-send gate logic.
- Initialize the tracking logs to start the first audit cycle.
Agent Stability Framework (ASF) Data Schema & Taxonomy
The framework uses a structured file-based approach to manage agent state and performance metrics:
| File Name | Purpose | Data Type |
|---|---|---|
| SOUL.md | Core identity and personality traits | Markdown |
| BASELINE_EXAMPLES.md | Gold-standard response templates | Markdown |
| DRIFT_LOG.md | Chronological tracking of personality decay | Log |
| FAULT_LOG.md | Record of hallucinations or technical failures | Log |
| STABILITY_LOG.md | Daily audit scores and health metrics | Table |
Agent Stability Framework (ASF) Advanced Features
- Multi-layer defense mechanism covering technical, behavioral, and essence-based failures.
- Model-agnostic architecture compatible with Claude, GPT, Gemini, Llama, and Mistral.
- Binary rule enforcement to reduce subjective judgment calls during self-audits.
- Intensifier detection to catch when an agent starts over-acting its persona.
- Integrated recovery protocols for automated self-correction when faults are detected.
SKILL.md
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