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 huaweicloud/huaweicloud-skills --skill huawei-cloud-cce-chaos-experimentgit clone --depth 1 https://github.com/huaweicloud/huaweicloud-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/huaweicloud/huaweicloud-skills/huawei-cloud-cce-chaos-experiment)<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-chaos-experiment"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-chaos-experiment/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/huaweicloud/huaweicloud-skills/huawei-cloud-cce-chaos-experiment"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-chaos-experiment.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 | $0.03730 |
| Opus 5.5 | $0.00061 | $0.01492 |
| Sonnet 5.5 | $0.00030 | $0.00746 |
| Haiku 4.5 | $0.00015 | $0.00373 |
Grade D, and why
huawei-cloud-cce-chaos-experiment scanned grade D with 3 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 27d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
sleep 1 && mv /tmp/kubectl_download /usr/local/bin/kubectl && chmod 755 /usr/local/bin/kubectl Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
hcloud CCE CreateKubernetesClusterCert --cluster_id=<id> --cli-region=<region> --duration=30 --cli-output=json > /root/.kube/config Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL "https://dl.k8s.io/release/v1.28.0/bin/linux/${ARCH}/kubectl" -o /tmp/kubectl_download How it starts
The opening of the file, as written. The whole thing — 339 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Huawei Cloud CCE AZ Power Outage Chaos Experiment
Overview
End-to-end CCE AZ power outage chaos experiment in three phases:
Phase 1: Prepare Phase 2: Execute Phase 3: Log Analysis
───────────── ────────────── ──────────────────
Discover clusters → Pre-check (nodes Ready) → Load experiment context
Select cluster Shutdown (BatchStop) Discover dependencies
Discover node AZs Monitor (Node/Pod) Collect logs (LTS + Pod)
Select target AZ Wait (duration) Analyze error patterns
Validate compatibility Rollback (BatchStart) Generate analysis report
Generate + deploy config Verify + report
Scenario: Shut down all CCE nodes in one AZ → Kubernetes marks nodes NotReady → Pods evicted and rescheduled to other AZs → start nodes back → verify recovery. Tests cluster HA under AZ-level failure.
Prerequisites
- hcloud CLI — installed and configured with AK/SK (ECS + CCE permissions)
- kubectl — installed and configured for CCE cluster access
- Python 3 — for discovery, validation, execution, and analysis scripts
- Environment variables:
HW_ACCESS_KEY,HW_SECRET_KEY,HW_REGION_NAME(optional, defaults to cn-north-4 if unset)
Run environment check:
bash scripts/check_env.sh
If kubectl is missing, check_env.sh auto-installs it. Manual install:
ARCH=$(uname -m | sed 's/x86_64/amd64/;s/aarch64/arm64/')
curl -fsSL "https://dl.k8s.io/release/v1.28.0/bin/linux/${ARCH}/kubectl" -o /tmp/kubectl_download
sleep 1 && mv /tmp/kubectl_download /usr/local/bin/kubectl && chmod 755 /usr/local/bin/kubectl
Phase 1: Prepare (故障演练准备)
Generates experiment configuration. Does NOT start the experiment.
Step 1.1: Environment Check
bash scripts/check_env.sh
Step 1.2: Determine Region [INTERACTIVE]
Check HW_REGION_NAME environment variable:
- Set → use that region (confirm with user: "Region is , correct?").
- Not set → ask the user which region to use. Do NOT silently default to
cn-north-4.
What ships with it
24 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.
- references/acceptance-criteria.md 6.7 KB
- references/analysis-workflow.md 3.1 KB
- references/cce-az-power-scenario.md 3.4 KB
- references/cce-validation-rules.md 3.7 KB
- references/cli-installation-guide.md 4.1 KB
- references/execution-workflow.md 4.6 KB
- references/experiment-template-guide.md 5.0 KB
- references/iam-policies.md 4.0 KB
- references/managed-service-logs.md 2.5 KB
- references/monitoring-guide.md 2.3 KB
- references/verification-method.md 6.6 KB
- scripts/analyze_logs.py 13 KB runs code
- scripts/check_env.sh 7.7 KB runs code
- scripts/collect_logs.py 16 KB runs code
- scripts/deploy_experiment.sh 4.4 KB runs code
- scripts/discover_cce.py 13 KB runs code
- scripts/discover_dependencies.py 5.3 KB runs code
- scripts/execute_experiment.py 15 KB runs code
- scripts/generate_analysis_report.py 8.5 KB runs code
- scripts/generate_experiment.py 9.0 KB runs code
- scripts/generate_report.py 6.4 KB runs code
- scripts/monitor_resources.py 7.7 KB runs code
- scripts/rollback_experiment.py 4.3 KB runs code
- scripts/validate_targets.py 10 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.
- 27d ago First seen · 339 lines · 152 tokens per session scan D 0929c67bbb04
huawei-cloud-cce-chaos-experiment is a skill published in the GitHub repository huaweicloud/huaweicloud-skills (59 stars, last pushed yesterday), licensed MIT. It adds 152 tokens to every session and 3,730 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it D with 3 findings (asks for root, reaches for credential files, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-01.
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