Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add proffesor-for-testing/agentic-qe --skill chaos-engineering-resiliencegit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/chaos-engineering-resilience)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/chaos-engineering-resilience"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/chaos-engineering-resilience/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/chaos-engineering-resilience"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/chaos-engineering-resilience.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.01126 |
| Opus 5.5 | $0.00016 | $0.00450 |
| Sonnet 5.5 | $0.00008 | $0.00225 |
| Haiku 4.5 | $0.00004 | $0.00113 |
Grade A, and why
chaos-engineering-resilience scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- chaos-engineering-resilience — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 164 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chaos Engineering & Resilience Testing
<default_to_action> When testing system resilience or injecting failures:
- DEFINE steady state (normal metrics: error rate, latency, throughput)
- HYPOTHESIZE system continues in steady state during failure
- INJECT real-world failures (network, instance, disk, CPU)
- OBSERVE and measure deviation from steady state
- FIX weaknesses discovered, document runbooks, repeat
Quick Chaos Steps:
- Start small: Dev → Staging → 1% prod → gradual rollout
- Define clear rollback triggers (error_rate > 5%)
- Measure blast radius, never exceed planned scope
- Document findings → runbooks → improved resilience
Critical Success Factors:
- Controlled experiments with automatic rollback
- Steady state must be measurable
- Start in non-production, graduate to production </default_to_action>
Quick Reference Card
When to Use
- Distributed systems validation
- Disaster recovery testing
- Building confidence in fault tolerance
- Pre-production resilience verification
Failure Types to Inject
| Category | Failures | Tools |
|---|---|---|
| Network | Latency, packet loss, partition | tc, toxiproxy |
| Infrastructure | Instance kill, disk failure, CPU | Chaos Monkey |
| Application | Exceptions, slow responses, leaks | Gremlin, LitmusChaos |
| Dependencies | Service outage, timeout | WireMock |
Blast Radius Progression
Dev (safe) → Staging → 1% prod → 10% → 50% → 100%
↓ ↓ ↓ ↓
Learn Validate Careful Full confidence
Steady State Metrics
| Metric | Normal | Alert Threshold |
|---|---|---|
| Error rate | < 0.1% | > 1% |
| p99 latency | < 200ms | > 500ms |
| Throughput | baseline | -20% |
Chaos Experiment Structure
// Chaos experiment definition
const experiment = {
name: 'Database latency injection',
hypothesis: 'System handles 500ms DB latency gracefully',
steadyState: {
errorRate: '< 0.1%',
p99Latency: '< 300ms'
},
method: {
type: 'network-latency',
target: 'database',
delay: '500ms',
duration: '5m'
},
rollback: {
automatic: true,
trigger: 'errorRate > 5%'
}
};
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 164 lines · 40 tokens per session scan A 2f6a1371957d
chaos-engineering-resilience is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (512 stars, last pushed yesterday), licensed MIT. It adds 40 tokens to every session and 1,126 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-11.
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