huawei-cloud-cce-metric-analyzer

huawei-cloud-cce-metric-analyzer is a skill for Claude Code, Codex from huaweicloud/huaweicloud-skills. It costs 293 tokens per session (7,401 once invoked), scanned A, original, MIT.

A Huawei Cloud CCE monitoring and analysis tool for metrics such as CPU, memory, disk use, requests, latency, connections, scaling, and errors. CCE is Huawei Cloud's managed Kubernetes service.

In plain words
What is it for?
Use it to inspect Pod, node, CoreDNS, ingress, autoscaler, control-plane, ECS, ELB, EIP, and NAT metrics, including cluster-wide monitoring summaries.
Why use it?
It turns collected measurements into threshold-based warnings and critical statuses, making unusual resource or service behavior easier to identify.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to inspect Pod, node, CoreDNS, ingress, autoscaler, control-plane, ECS, ELB, EIP, and NAT metrics, including cluster-wide monitoring summaries.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-metric-analyzer
Install

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.

Any agent
npx skills add huaweicloud/huaweicloud-skills --skill huawei-cloud-cce-metric-analyzer
Clone the repo
git clone --depth 1 https://github.com/huaweicloud/huaweicloud-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for huawei-cloud-cce-metric-analyzer

README.md
[![agentmods](https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-metric-analyzer/github.svg)](https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-metric-analyzer)
Your own site
<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-metric-analyzer"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-metric-analyzer/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.

agentmods 80×15 button for huawei-cloud-cce-metric-analyzer

Your own site · 80×15
<a href="https://agentmods.dev/skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-metric-analyzer"><img src="https://agentmods.dev/badge/skills/huaweicloud/huaweicloud-skills/huawei-cloud-cce-metric-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 293 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 7,401 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 3 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Privilege Escalation · line 105
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • high Privilege Escalation · line 229
    Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.
    Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
  • medium Excessive Agency · line 99
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00293 $0.07401
Opus 5 $0.00147 $0.03700
Sonnet 5 $0.00059 $0.01480
Haiku 4.5 $0.00029 $0.00740

Measured 12d ago against content hash a4d81274d5e0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

huawei-cloud-cce-metric-analyzer scanned grade A with 1 finding 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 12d ago.

The scan reads SKILL.md. This mod also ships 12 executable files (scripts/huawei_cloud/__init__.py, scripts/huawei_cloud/aom.py, scripts/huawei_cloud/cce_cluster_monitoring.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

> **Execution method**: Cloud service queries are executed through the local `hcloud` CLI. AOM Prometheus `query_range` calls are the only exception and use signed HTTPS requests because the required Prometheus range-que
skills/container/cce/huawei-cloud-cce-metric-analyzer/SKILL.md · 488 lines

How it starts

The opening of the file, as written. The whole thing — 488 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Huawei Cloud CCE Metric Analyzer

Overview

Query and analyze metrics for CCE clusters (Pod/Node CPU/memory/disk) and cloud resources (ECS, ELB, EIP, NAT). Supports threshold-based anomaly detection, status classification (critical/warning/normal), and full-cluster monitoring aggregation.

Architecture: python3 scripts/huawei-cloud.py dispatcher → hcloud (KooCLI) cloud service queries + signed AOM Prometheus HTTP queries + limited kubectl reads only when Kubernetes resource relationships are required → Pod/Node metrics, ECS/ELB/EIP/NAT metrics → Threshold classification → Anomaly detection

Execution method: Cloud service queries are executed through the local hcloud CLI. AOM Prometheus query_range calls are the only exception and use signed HTTPS requests because the required Prometheus range-query path is not compatible with hcloud. Do not call Huawei Cloud SDKs, curl IAM flows, openstack, or hand-written cloud APIs outside the bundled dispatcher.

Related Skills: use pod/node diagnosers, Kubernetes event analyzer, capacity/cost skills, or auto-remediation runner for follow-up diagnosis or explicitly requested remediation.

Capabilities:

  • Pod CPU/memory TopN ranking and single Pod time-series metrics
  • Node CPU/memory/disk TopN ranking and single Node time-series metrics
  • Node GPU and xGPU metrics, including GPU utilization, memory, temperature, power, schedule policy, xGPU allocation, usage, and health
  • CoreDNS QPS, error rate excluding NXDOMAIN, NXDOMAIN rate, P95 latency, replica count, and per-Pod CPU/memory metrics
  • nginx-ingress QPS, 4xx/5xx rate, success rate, P95 latency, active connections, per-Pod CPU/memory, and Ingress TLS certificate expiration status
  • Autoscaler unschedulable Pods, node state count, scale-up/down events, errors, node groups, HPA current/desired replicas, and per-Pod CPU/memory metrics
  • Kubernetes control-plane metrics for apiserver, etcd, controller-manager, and scheduler
  • ECS instance CPU/memory/disk/network metrics
  • ELB connection, bandwidth, QPS metrics
  • EIP bandwidth, traffic, packet loss metrics
  • NAT Gateway SNAT connection metrics
  • Full-cluster monitoring aggregation with anomaly detection (80% threshold)
  • Threshold-based status classification (critical/warning/normal/unknown)

Read the full file on GitHub · 488 lines

Changes

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.

  1. 12d ago First seen · 488 lines · 293 tokens per session scan A a4d81274d5e0

Subscribe to this mod's changes

huawei-cloud-cce-metric-analyzer is a skill published in the GitHub repository huaweicloud/huaweicloud-skills (49 stars, last pushed yesterday), licensed MIT. It adds 293 tokens to every session and 7,401 once invoked, about $0.0015 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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