An autonomous SRE agent that detects, diagnoses, and heals production infrastructure β then learns from every incident it resolves.
Built on Hermes Agent by NousResearch. Submitted for the "Show us what Hermes Agent can do" challenge.
When a production server goes down at 3 AM, an on-call engineer has to:
- Wake up, check alerts
- SSH in, run diagnostics manually
- Piece together root cause from logs
- Apply a fix - hopefully the right one
- Verify it worked
- Write a post-mortem nobody will read
Mean time to resolve (MTTR) for P0 incidents averages 45β60 minutes. Much of that is humans doing things a sufficiently capable agent could do faster and better.
Hermes Incident Commander does all of it - autonomously, in minutes, getting smarter with each incident it handles.
# Install dependencies
pip install anthropic rich
# Set your API key
export ANTHROPIC_API_KEY=sk-ant-...
# Run a demo incident (disk full scenario)
python demo/demo_incident.py --scenario disk-full-logs
# Try other scenarios
python demo/demo_incident.py --scenario svc-crash-nginx
python demo/demo_incident.py --scenario cpu-runaway-processWhat you'll see:
- Hermes detects the incident and classifies severity (P0/P1/P2/P3)
- Runs parallel diagnostics across CPU, memory, disk, and services
- Identifies root cause with explicit reasoning
- Applies the safest effective fix
- Verifies the fix worked
- Writes a structured post-incident report to
~/.hermes/incidents/ - Creates a new prevention skill in
~/.hermes/skills/so it handles this faster next time
This project was designed to push every capability of Hermes Agent:
| Hermes Feature | How It's Used |
|---|---|
| Persistent Memory | Builds a system topology map over time. Learns which services fail together, time-of-day patterns, and which remediations work on YOUR infrastructure. |
| Skill Auto-Creation | After every novel incident, writes a new SKILL.md prevention playbook. Hermes gets measurably better at your stack over weeks. |
| Cron Scheduler | Every 5 min: critical health check. Every hour: full audit. Daily 08:00: morning briefing to Telegram. |
| Gateway (Telegram/Discord) | Real-time P0 alerts, resolution notices, and daily briefings delivered to your phone. |
| Subagent Spawning | For multi-service environments, spawns parallel subagents to investigate nginx, database, and application layers simultaneously. |
| Session Search (FTS5) | "Have we seen this error before?" - searches past incidents for matching patterns. |
| execute_code | Collapses multi-step diagnostic pipelines into single inference turns, dramatically reducing latency. |
| MCP Integration | Connects to cloud provider APIs (AWS/GCP/Azure MCP servers) for auto-scaling and cloud-native remediation. |
flowchart TD
ALERT([π¨ Incident Alert]) --> DETECT
DETECT["π DETECT<br/>Gather system vitals<br/>CPU β’ Memory β’ Disk β’ Services"]
TRIAGE["βοΈ TRIAGE<br/>Classify severity<br/>P0 Β· P1 Β· P2 Β· P3"]
DIAGNOSE["π¬ DIAGNOSE<br/>Root cause analysis<br/>Logs Β· Processes Β· Stack traces"]
REMEDIATE["π§ REMEDIATE<br/>Apply safest fix<br/>Tier 1 β 2 β 3"]
VERIFY["β
VERIFY<br/>Confirm resolution<br/>Before vs after metrics"]
DETECT --> TRIAGE --> DIAGNOSE --> REMEDIATE --> VERIFY
CRON["β±οΈ CRON<br/>Every 5 min: health check<br/>Every hour: full audit<br/>Daily 08:00: briefing"]
CRON -->|triggers| DETECT
LEARN["π§ LEARN<br/>Write post-incident report<br/>Create prevention SKILL.md<br/>Update MEMORY.md<br/>Search past incidents (FTS5)"]
VERIFY --> LEARN
GATEWAY["π² GATEWAY<br/>Telegram Β· Discord Β· Slack"]
TRIAGE -->|"π¨ P0/P1 alert"| GATEWAY
VERIFY -->|"β
resolved"| GATEWAY
CRON -->|"π daily briefing"| GATEWAY
style DETECT fill:#1e3a5f,color:#fff
style TRIAGE fill:#7b2d00,color:#fff
style DIAGNOSE fill:#1e3a5f,color:#fff
style REMEDIATE fill:#1a4731,color:#fff
style VERIFY fill:#1a4731,color:#fff
style LEARN fill:#3d2068,color:#fff
style CRON fill:#2d2d2d,color:#fff
style GATEWAY fill:#2d2d2d,color:#fff
style ALERT fill:#7b2d00,color:#fff
graph LR
ROOT["π hermes-incident-commander"]
ROOT --> SKILLS["π skills/"]
ROOT --> ENVS["π environments/"]
ROOT --> DEMO["π demo/"]
ROOT --> TESTS["π tests/"]
ROOT --> DOCS["π docs/"]
ROOT --> REQ["π requirements.txt"]
SKILLS --> SKILL_MD["π incident-commander/SKILL.md<br/>β install into ~/.hermes/skills/"]
ENVS --> ENV_PY["π incident_env.py<br/>β Atropos RL environment"]
ENVS --> ENV_CFG["βοΈ incident_config.yaml<br/>β training configuration"]
DEMO --> DEMO_PY["π demo_incident.py<br/>β standalone demo"]
TESTS --> TEST_PY["π test_incident_env.py<br/>β pytest test suite"]
DOCS --> SETUP["π SETUP.md"]
DOCS --> WRITEUP["π WRITEUP.md"]
style ROOT fill:#1e3a5f,color:#fff
style SKILL_MD fill:#1a4731,color:#fff
style ENV_PY fill:#3d2068,color:#fff
style DEMO_PY fill:#7b2d00,color:#fff
style TEST_PY fill:#2d2d2d,color:#fff
curl -fsSL https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh | bashhermes setup # Interactive setup wizard
hermes model # Choose your model (Nous Portal recommended)
hermes gateway setup # Connect Telegram/Discord for alerts# Copy the skill to Hermes's skills directory
cp -r skills/incident-commander ~/.hermes/skills/
# Verify it's loaded
hermes
> /skillsIn your Hermes conversation:
Set up incident monitoring: run a health check every 5 minutes and alert me
on Telegram if anything is P0 or P1. Send me a daily briefing at 08:00.
Hermes will install the cron jobs automatically.
# Install Atropos
pip install atroposlib
# Generate SFT training data
python environments/incident_env.py process --config environments/incident_config.yaml
# Full RL training (requires VLLM)
python environments/incident_env.py serve --config environments/incident_config.yamlThe training environment uses a multi-component reward that captures real SRE quality:
pie title Reward Components
"Resolution β Did the incident get fixed?" : 50
"RCA Quality β Root cause explained?" : 15
"Report Quality β Post-mortem written?" : 15
"Skill Created β Prevention skill added?" : 10
"Response Speed β Fast MTTR?" : 5
"Tool Efficiency β Minimal tool calls?" : 5
| ID | Severity | Category | Description |
|---|---|---|---|
svc-crash-nginx |
P0 | service | nginx crashed, website unreachable |
disk-full-logs |
P1 | disk | 95% disk usage from exploded log files |
memory-leak-process |
P1 | memory | Mystery process eating 150MB+ |
cpu-runaway-process |
P2 | cpu | 95% CPU from runaway computation |
failed-systemd-unit |
P2 | service | Custom worker service in failed state |
# Install test dependencies
pip install pytest pytest-asyncio
# Run full test suite
pytest tests/ -v
# Run specific test classes
pytest tests/test_incident_env.py::TestScenarioDefinitions -v
pytest tests/test_incident_env.py::TestRewardFunction -v
pytest tests/test_incident_env.py::TestSkillFile -v-
Real problem, real impact. P0 incidents cost companies thousands of dollars per minute. Shaving 30 minutes off MTTR with an autonomous agent is immediately valuable.
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Uses every Hermes capability. Memory, skills, cron, gateway, subagents, session search, execute_code - all integrated into a coherent, meaningful workflow.
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Self-improving. The longer Hermes runs, the better it gets at your specific infrastructure. This is Hermes's core promise - "the agent that grows with you" - demonstrated concretely.
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Closes the training loop. The Atropos RL environment means this isn't just a demo - it's a path to training models that are genuinely better at agentic SRE tasks.
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Ships with working code. The demo runs standalone, the tests pass, and the skill file installs in one command.
MIT
Built with Hermes Agent - the agent that grows with you.