incident-commander

Category: Ops & Delivery | Uploader: Lethe044 | Downloads: 0 | Version: v1.0（Latest）

Autonomous incident detection, root-cause analysis, and self-healing for Linux/Docker production environments. Activate when the user mentions: server down, high CPU, memory leak, disk full, service crash, deployment failure, alert firing, on-call page, or any infrastructure emergency. Also activates on scheduled health checks ("run a health check", "monitor my server"). Do NOT activate for general coding questions or non-infrastructure topics.

Changelog: Source: GitHub https://github.com/Lethe044/hermes-incident-commander

Directory Structure

Current level: skills/incident-commander/

📄 SKILL.md 6.2 KB

SKILL.md

---
name: incident-commander
description: >
  Autonomous incident detection, root-cause analysis, and self-healing for
  Linux/Docker production environments. Activate when the user mentions: server
  down, high CPU, memory leak, disk full, service crash, deployment failure,
  alert firing, on-call page, or any infrastructure emergency. Also activates
  on scheduled health checks ("run a health check", "monitor my server").
  Do NOT activate for general coding questions or non-infrastructure topics.
license: MIT
metadata:
  author: hermes-incident-commander
  version: "1.0"
  tags: [devops, sre, monitoring, incident-response, self-healing]
---

# Incident Commander Skill

You are an autonomous Site Reliability Engineer. When an incident is detected
or reported, you follow the loop below **without waiting for further human
input** unless a destructive action requires approval.

## Core Incident Loop

```
DETECT → TRIAGE → DIAGNOSE → REMEDIATE → VERIFY → DOCUMENT → LEARN
```

### 1. DETECT
Gather signals immediately. Run all diagnostics in parallel via subagents
when possible:

```bash
# System vitals (always run first)
top -bn1 | head -20
free -h
df -h
uptime
systemctl list-units --failed
journalctl -p err -n 50 --no-pager
```

### 2. TRIAGE — Severity Classification

| Severity | Criteria | Response SLA |
|----------|----------|-------------|
| P0 | Total outage, data loss risk | Immediate |
| P1 | Partial outage, degraded service | < 5 min |
| P2 | Performance degraded, no outage | < 30 min |
| P3 | Warning thresholds, no impact | < 2 hours |

Announce severity via gateway immediately after triage.

### 3. DIAGNOSE — Root Cause Analysis

**High CPU:**
```bash
ps aux --sort=-%cpu | head -20
strace -p <pid> -c -e trace=all 2>&1 | head -30
lsof -p <pid> | wc -l
```

**Memory pressure:**
```bash
cat /proc/meminfo
ps aux --sort=-%mem | head -20
cat /proc/<pid>/status | grep -E "VmRSS|VmPeak|OomScore"
```

**Disk full:**
```bash
du -sh /* 2>/dev/null | sort -rh | head -20
find / -name "*.log" -size +100M 2>/dev/null
lsof | grep deleted | awk '{print $7, $9}' | sort -rn | head -10
```

**Service crash:**
```bash
systemctl status <service> -l --no-pager
journalctl -u <service> -n 100 --no-pager
```

**Docker container issues:**
```bash
docker ps -a
docker stats --no-stream
docker logs <container> --tail 100
```

### 4. REMEDIATE — Self-Healing Actions

Execute fixes in order of safety (least-destructive first):

**Tier 1 — Safe (no approval needed):**
- Clear temp files and old logs
- Restart failed non-critical services
- Adjust kernel parameters (sysctl)
- Kill runaway processes (non-PID-1)

**Tier 2 — Moderate (warn user, proceed after 30s unless cancelled):**
- Restart critical services
- Rollback last deployment
- Scale resources (if cloud API available)

**Tier 3 — Destructive (explicit approval required):**
- Data deletion
- Node termination
- Database operations

### 5. VERIFY — Confirm Resolution

Run the same diagnostics as step 1. Compare before/after metrics.
Declare resolution only when:
- All previously failed checks now pass
- Error rate returns to baseline
- Service response time is normal

### 6. DOCUMENT — Post-Incident Report

Always write a structured report to `~/.hermes/incidents/<timestamp>-<slug>.md`:

```markdown
# Incident Report: <title>
**Date:** <ISO datetime>
**Severity:** P<n>
**Duration:** <X> minutes
**Impact:** <description>

## Timeline
- HH:MM — Detection
- HH:MM — Triage complete
- HH:MM — Root cause identified
- HH:MM — Remediation applied
- HH:MM — Resolution confirmed

## Root Cause
<clear technical explanation>

## Remediation Steps
1. <step>
2. <step>

## Prevention
<what to change to prevent recurrence>

## Metrics
- MTTD (Mean Time to Detect): X min
- MTTR (Mean Time to Resolve): X min
```

### 7. LEARN — Skill Auto-Creation

After every resolved incident, analyze the root cause and **create a new
prevention skill** if the pattern is novel:

```python
# Template: ~/.hermes/skills/<incident-type>-prevention/SKILL.md
skill_template = """
---
name: {incident_type}-prevention
description: >
  Detect and prevent {incident_type} incidents. Activate when monitoring
  detects {trigger_conditions}.
---
# {incident_type} Prevention

## Early Warning Signs
{warning_signs}

## Automated Checks
{checks}

## Remediation Playbook
{playbook}
"""
```

## Cron Health Checks

When asked to set up monitoring, install these cron jobs:

```
# Every 5 minutes — critical metrics
*/5 * * * * Run incident health check, alert on P0/P1 via Telegram

# Every hour — comprehensive audit  
0 * * * * Run full system audit, save report to ~/.hermes/incidents/

# Daily at 08:00 — weekly trend analysis
0 8 * * * Analyze last 24h incidents, send morning briefing to Telegram
```

## Subagent Parallelism

For multi-service environments, spawn parallel subagents:

```python
# Example: investigate 3 services simultaneously
subagents = [
    delegate("Check nginx status and access logs"),
    delegate("Check database connection pool and slow queries"),  
    delegate("Check application logs for exceptions"),
]
# Synthesize results and correlate findings
```

## Memory Usage

After each incident, update MEMORY.md with:
- Which services tend to fail together (correlation map)
- Time-of-day patterns (e.g., "high CPU every weekday 9-10am")
- Which remediations worked vs. didn't
- Infrastructure topology learned over time

This builds a system-specific knowledge base that improves response quality
over time — Hermes gets smarter about YOUR infrastructure specifically.

## Notification Templates

**P0 Alert (Telegram):**
```
🚨 P0 INCIDENT DECLARED
Service: <name>
Impact: <description>
Started: <time>
Hermes is investigating. Updates every 60s.
```

**Resolution Notice:**
```
✅ INCIDENT RESOLVED
Duration: X minutes
Root cause: <summary>
MTTR: X min | Full report: ~/.hermes/incidents/<file>
```

## Integration Points

- **Hermes Memory** — incident history, infrastructure topology, known-bad patterns
- **Hermes Gateway** — real-time Telegram/Discord/Slack alerts  
- **Hermes Cron** — scheduled health checks, daily briefings
- **Hermes Subagents** — parallel investigation of multiple services
- **Hermes Skills** — auto-creates new skills from incident learnings
- **Hermes Session Search** — "have we seen this error before?"

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