aegis-protocol

Self-healing stability monitor for AI agents - 5 core checks + 15 extended checks, auto-recovery, health scoring

3,891 stars

Best use case

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

Self-healing stability monitor for AI agents - 5 core checks + 15 extended checks, auto-recovery, health scoring

Teams using aegis-protocol 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/aegis-protocol/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/ankechenlab-node/aegis-protocol/SKILL.md"

Manual Installation

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

How aegis-protocol Compares

Feature / Agentaegis-protocolStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Self-healing stability monitor for AI agents - 5 core checks + 15 extended checks, auto-recovery, health scoring

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.

Related Guides

SKILL.md Source

# Aegis Protocol 🛡️

**Self-Healing Stability Monitor for AI Agents**

**Version**: 0.12.6  
**Author**: Dream  
**License**: MIT

---

## Features

- **20-Dimension Monitoring**: System, services, AI agent, security, maintenance
- **Auto Recovery**: Terminate stuck sessions, restart services, compact context
- **Health Scoring**: Quantified health score (0-100)
- **Healing Memory**: Record and learn from recovery strategies
- **Result Caching**: 5-minute TTL for reduced system calls

---

## Commands

### `aegis-protocol init`
Initialize configuration file

### `aegis-protocol status`
Show system health summary

### `aegis-protocol check`
Run full health check

### `aegis-protocol heal`
Execute automatic recovery

### `aegis-protocol config`
View current configuration

---

## Usage Examples

```bash
# Initialize
python3 aegis-protocol.py init

# Check health
python3 aegis-protocol.py check

# Auto recover
python3 aegis-protocol.py heal

# View config
python3 aegis-protocol.py config
```

---

## Configuration

File: `~/.openclaw/workspace/.watchdog-config.json`

```json
{
  "thresholds": {
    "sessionTimeoutMinutes": 60,
    "pm2RestartAlert": 50,
    "diskUsagePercent": 90,
    "memoryUsagePercent": 95,
    "contextUsagePercent": 80
  }
}
```

---

## Monitoring Dimensions

| Category | Checks |
|----------|--------|
| System | CPU, Memory, Disk, Zombies, FD, Connections |
| Services | PM2, Nginx, Docker, Cron |
| AI Agent | Sessions, Context, Tasks, Loops |
| Security | SSL, Updates, Git |
| Maintenance | Backup, Cleanup, Network |

---

## Health Score

| Score | Status |
|-------|--------|
| 90-100 | Excellent |
| 70-89 | Good |
| 50-69 | Warning |
| 0-49 | Critical |

---

## Testing

```bash
# Unit tests
python3 -m pytest tests/ -v

# Coverage
python3 -m pytest tests/ --cov=aegis_protocol -v
```

**Coverage**: 82%  
**Tests**: 20+ passing

---

## Quality Metrics

| Metric | Value |
|--------|-------|
| Type hints | >90% |
| Test coverage | 82% |
| Documentation | 100% |
| Bugs | 0 |

---

## Version History

### v0.7.0 (2026-04-05)
- Result caching with 5-minute TTL
- Type hints >90% coverage
- Exception classification (4 types)
- 20-dimension monitoring
- Health scoring system

---

*Aegis Protocol - The Never-Sleeping Guardian* 🌀

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