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 elproximoframework/Skills_Ingenieria --skill chaos-engineeringgit clone --depth 1 https://github.com/elproximoframework/Skills_IngenieriaWrote 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/elproximoframework/skills_ingenieria/chaos-engineering)<a href="https://agentmods.dev/skills/elproximoframework/skills_ingenieria/chaos-engineering"><img src="https://agentmods.dev/badge/skills/elproximoframework/skills_ingenieria/chaos-engineering/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/elproximoframework/skills_ingenieria/chaos-engineering"><img src="https://agentmods.dev/badge/skills/elproximoframework/skills_ingenieria/chaos-engineering.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 | $0.00152 | $0.02504 |
| Opus 5 | $0.00076 | $0.01252 |
| Sonnet 5 | $0.00030 | $0.00501 |
| Haiku 4.5 | $0.00015 | $0.00250 |
Grade A, and why
chaos-engineering 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 7d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
9 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.
- assets/experiment_template.md 2.4 KB
- assets/postmortem_template.md 1.5 KB
- references/attack_taxonomy.md 5.7 KB
- references/chaos_principles.md 5.3 KB
- references/experiment_design.md 5.6 KB
- references/tooling_landscape.md 6.1 KB
- scripts/blast_radius_calculator.py 4.9 KB runs code
- scripts/experiment_designer.py 6.3 KB runs code
- scripts/experiment_postmortem.py 5.1 KB runs code
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.
- 7d ago First seen · 232 lines · 152 tokens per session scan A fde41aeb8b99
chaos-engineering is a skill published in the GitHub repository elproximoframework/Skills_Ingenieria (2 stars, last pushed 2mo ago), with no licence file. It adds 152 tokens to every session and 2,504 once invoked, about $0.0008 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 2026-09-03.
Other skills, from other repositories
chaos-engineering
Use when planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin", "AWS FIS", or any deliberate failure-injection question.…
chaos-engineering
Use when planning, running, or learning from chaos engineering experiments. Triggers on "chaos experiment", "fault injection", "gameday", "resilience test", "blast radius", "steady state", "abort criteria", "Chaos Toolkit", "Chaos Mesh", "Litmus", "Gremlin", "AWS FIS", or any deliberate failure-injection question.…
chaos-engineering-expert
Expert in chaos engineering principles, failure injection, resilience testing, Chaos Monkey, Gremlin, and building fault-tolerant systems. Use when the user mentions reliability, testing, SRE, resilience, failure injection, or resilience testing, or when the task involves Chaos Engineering Principles, Failure Types…
Advanced Chaos Engineering
Advanced chaos engineering patterns using Chaos Monkey, Litmus, and Gremlin for testing distributed system resilience under failure conditions.
Kubernetes Chaos Testing
Chaos testing for Kubernetes workloads using Chaos Mesh, Litmus, and custom fault injection for pod, network, and disk failures.
chaos-fault-injection
Deliberately inject faults — dropped connections, corrupted writes, latency, malformed responses, resource exhaustion — and assert the system's expected recovery (escalation, hardstop, rollback).