chaos

name	chaos
description	Injects controlled faults for resilience testing on non-prod. Triggers: chaos, fault injection, latency injection, dependency kill, resilience test.
effort	medium
disable-model-invocation	true
argument-hint	[target]
context	fork
agent	chaos-monkey
allowed-tools	Bash, Read

Chaos Command

$ARGUMENTS

Triggers a controlled resilience experiment.

Usage

/chaos <experiment> [target]
# Example: /chaos latency backend-api
# Example: /chaos kill redis

Protocol

1. Safety Check: Verify env != PROD.
2. Baseline: Check system health is green.
3. Inject: Run the fault injection.
4. Observe: Monitor logs/metrics for 60s.
5. Recover: Restore system health.
6. Report: Did we survive?

Rules

• MUST verify target environment is non-production before injecting
• NEVER run against a system without a healthy baseline
• CRITICAL: abort immediately if recovery does not complete within the observation window
• MANDATORY: log every injected fault with timestamp and scope

Gotchas

• NODE_ENV=production on a developer's machine is common — checking that env var alone is not enough proof of non-prod. Combine with kubeconfig context, cloud account ID, or a project-specific env file check before injecting.
• docker stats reports cached values; the first sample immediately after injection is often pre-fault. Wait at least 5 seconds before reading metrics.
• Kubernetes liveness probes may self-heal the faulted pod inside the 60s observation window — the report shows green while the workload is still flapping. Check pod restart counters, not just health endpoints.
• Latency injected with tc (Linux traffic control) persists across container restarts on the host and across SIGTERM. Always pair the inject step with an explicit tc qdisc del dev <iface> root cleanup in the recover step — the fork context will not undo it for you.

When NOT to Use

• In production without an explicit, written runbook — use /workflow incident-response for real incidents
• When the system has no observability (no metrics, no logs) — fix observability first
• For load testing — use dedicated load-test tooling, not chaos injection
• During an active incident — stabilize first with /panic, then investigate