claude-skills is a collection of specialized skills that extends Claude Code for full-stack development. Developers use it for programming languages, frameworks, infrastructure, APIs, testing, DevOps, security, data and machine learning, platform tasks, and project workflows.
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 Jeffallan/claude-skills --skill chaos-engineergit clone --depth 1 https://github.com/Jeffallan/claude-skillsWrote 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/jeffallan/claude-skills/chaos-engineer)<a href="https://agentmods.dev/skills/jeffallan/claude-skills/chaos-engineer"><img src="https://agentmods.dev/badge/skills/jeffallan/claude-skills/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/skills/jeffallan/claude-skills/chaos-engineer"><img src="https://agentmods.dev/badge/skills/jeffallan/claude-skills/chaos-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket warn
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00088 | $0.01626 |
| Opus 5.5 | $0.00035 | $0.00650 |
| Sonnet 5.5 | $0.00018 | $0.00325 |
| Haiku 4.5 | $0.00009 | $0.00163 |
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 27d 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 — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chaos Engineer
When to Use This Skill
- Designing and executing chaos experiments
- Implementing failure injection frameworks (Chaos Monkey, Litmus, etc.)
- Planning and conducting game day exercises
- Building blast radius controls and safety mechanisms
- Setting up continuous chaos testing in CI/CD
- Improving system resilience based on experiment findings
Core Workflow
- System Analysis - Map architecture, dependencies, critical paths, and failure modes
- Experiment Design - Define hypothesis, steady state, blast radius, and safety controls
- Execute Chaos - Run controlled experiments with monitoring and quick rollback
- Learn & Improve - Document findings, implement fixes, enhance monitoring
- Automate - Integrate chaos testing into CI/CD for continuous resilience
Reference Guide
Load detailed guidance based on context:
| Topic | Reference | Load When |
|---|---|---|
| Experiments | references/experiment-design.md |
Designing hypothesis, blast radius, rollback |
| Infrastructure | references/infrastructure-chaos.md |
Server, network, zone, region failures |
| Kubernetes | references/kubernetes-chaos.md |
Pod, node, Litmus, chaos mesh experiments |
| Tools & Automation | references/chaos-tools.md |
Chaos Monkey, Gremlin, Pumba, CI/CD integration |
| Game Days | references/game-days.md |
Planning, executing, learning from game days |
Safety Checklist
Non-obvious constraints that must be enforced on every experiment:
- Steady state first — define and verify baseline metrics before injecting any failure
- Blast radius cap — start with the smallest possible impact scope; expand only after validation
- Automated rollback ≤ 30 seconds — abort path must be scripted and tested before the experiment begins
- Single variable — change only one failure condition at a time until behaviour is well understood
- No production without safety nets — customer-facing environments require circuit breakers, feature flags, or canary isolation
- Close the loop — every experiment must produce a written learning summary and at least one tracked improvement
What ships with it
5 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.
- 27d ago Changed · +3 lines 97b9db30c0b8
- 2mo ago First seen · 185 lines · 88 tokens per session scan A 80619e93302d
chaos-engineer is a skill published in the GitHub repository Jeffallan/claude-skills (12,126 stars, last pushed yesterday), licensed MIT. It adds 88 tokens to every session and 1,626 once invoked, about $0.0004 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 2026-08-30.
Other skills, from other repositories
skill-tester
Runs TDD pressure scenarios against a skill before and after it is written, proving the skill actually changes agent behaviour instead of merely reading well. Use when verifying a new or edited skill has real effect, establishing a RED baseline before authoring, or confirming a GREEN result after.
dotnet-test-api
Manages external API tests for .NET solutions using xUnit + Flurl.Http + FluentAssertions, with a shared IAsyncLifetime fixture that authenticates once per test session. Creates a dedicated .ApiTests project (separate from .Tests for unit tests). Default auth scheme is Generic JWT Bearer; NAuth, OAuth2…
dotnet-test
Manages unit tests using xUnit in .NET projects. Creates the test project if it doesn't exist, organizes tests by layer (Domain, Application, Infra, API), mirrors the source folder structure, and generates test files. Use when creating, updating, or organizing unit tests.
critique
Adversarial design critique of the current work. Render it, look at it, and argue for rejection. Run after the gates are green, never instead of them.
ship
Pre-release gate. Run the full gate, responsive + render checks, then produce the release checklist (README badge/current/changelog). Use before tagging a release.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.