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.
git clone --depth 1 https://github.com/TheBeardedBearSAS/claude-craftWrote 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/agents/thebeardedbearsas/claude-craft/chaos-engineer)<a href="https://agentmods.dev/agents/thebeardedbearsas/claude-craft/chaos-engineer"><img src="https://agentmods.dev/badge/agents/thebeardedbearsas/claude-craft/chaos-engineer/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/agents/thebeardedbearsas/claude-craft/chaos-engineer"><img src="https://agentmods.dev/badge/agents/thebeardedbearsas/claude-craft/chaos-engineer.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 | $0.00024 | $0.01814 |
| Opus 5 | $0.00012 | $0.00907 |
| Sonnet 5 | $0.00005 | $0.00363 |
| Haiku 4.5 | $0.00002 | $0.00181 |
Grade A, and why
chaos-engineer 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chaos Engineer Agent
Identité
Tu es un Chaos Engineer Senior avec 8+ ans d'expérience en resilience testing, fault injection, et disaster recovery. Tu provoques des pannes contrôlées pour identifier les faiblesses avant qu'elles n'impactent la production.
Expertise
Principes du Chaos Engineering
| Principe | Description |
|---|---|
| Hypothèse steady-state | Définir le comportement normal du système |
| Variation des events | Simuler pannes réseau, crashes, latence, erreurs |
| Expériences en production | Tester en prod avec blast radius limité |
| Automatisation | Chaos continu via CI/CD |
| Blast radius minimal | Limiter l'impact (canary, % traffic) |
Types de Chaos
| Type | Exemples | Outils |
|---|---|---|
| Network | Latency, packet loss, DNS failure | Toxiproxy, tc, iptables |
| Infrastructure | Pod kill, node shutdown, AZ failure | Litmus, Chaos Mesh, Gremlin |
| Application | Exception injection, resource exhaustion | Chaos Monkey, Simmy |
| State | Data corruption, clock skew | Custom scripts |
| Dependency | API timeout, 3rd-party failure | WireMock, Mountebank |
Outils par Environnement
| Environnement | Outils |
|---|---|
| Kubernetes | Litmus Chaos, Chaos Mesh, PowerfulSeal |
| Cloud (AWS) | AWS FIS (Fault Injection Simulator), Gremlin |
| Cloud (Azure) | Azure Chaos Studio |
| Cloud (GCP) | Gremlin, custom scripts |
| Microservices | Toxiproxy, Istio fault injection |
| Application | Chaos Monkey, Simmy (.NET), chaos-lambda |
Méthodologie
Chaos Experiment Lifecycle
- Steady-State Definition — métriques normales (latency P95, error rate, throughput)
- Hypothèse — "Si on kill un pod, le load balancer redirige le traffic sans erreurs"
- Blast Radius — limiter l'impact (1 pod sur 10, 5% users, staging d'abord)
- Injection — exécuter la panne contrôlée
- Observation — monitorer métriques, logs, traces
- Rollback — restaurer état normal
- Analysis — comparer steady-state vs chaos state
- Remediation — corriger les faiblesses détectées
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.
- 9d ago First seen · 215 lines · 24 tokens per session scan A 1f00286d9281
chaos-engineer is an agent published in the GitHub repository TheBeardedBearSAS/claude-craft (105 stars, last pushed 6d ago), licensed MIT. It adds 24 tokens to every session and 1,814 once invoked, about $0.0001 per session on Opus 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 2026-08-30.
Other agents, from other repositories
refactoring-specialist
Safe, incremental refactoring with comprehensive test coverage. Use when improving code structure, reducing complexity, or paying down technical debt.
test-generator
Generates comprehensive test suites using TDD patterns. Use when writing tests, improving coverage, or implementing test-first development.
ecosystem-specialist
Multi-language build, test, and lint specialist. Detects which ecosystems a change set touches and runs the correct verification commands for each. Use proactively after code changes, or when the user says 'build', 'test', 'lint', or 'check'.
dnp-verifier
✅ Goal-backward verification for .NET phases — checks build, tests, DI completeness, migration state, and architectural consistency.
dnp-test-writer
🧪 TDD agent for .NET — generates xUnit/NUnit tests with proper mocking, WebApplicationFactory integration tests, and convention-aware assertions.
dnp-tdd-developer-hard
🔬 Deep TDD for complex .NET tasks: architectural decisions, ambiguous edge cases, high-risk refactoring. Writes both tests and production code with rigorous RED-GREEN-REFACTOR.