wifi-troubleshooting

针对无线场景下终端体验差、网卡、无法接入 WiFi 等问题进行排障

Security Scan

The skill's behavior (calling Cloudnet APIs via an npm-installed CLI and requiring a Cloudnet API key) matches its stated purpose, but metadata inconsistencies and the need to install/run an external npm package (mcporter) mean you should be cautious before granting credentials or installing it.

Purpose & Capability

The skill is intended to diagnose Wi‑Fi issues using Cloudnet and the instructions call the mcporter CLI to invoke cloudnet-mcp APIs — that matches the stated purpose. However there is an internal naming mismatch (registry skill name 'wifi-troubleshooting' vs SKILL.md name 'cloudnet-analyze') and the registry summary lists "Required env vars: none" while the SKILL.md and metadata require CLOUDNET_API_KEY. These inconsistencies should be clarified.

Instruction Scope

Runtime instructions are narrowly scoped to: install mcporter, configure a Cloudnet MCP connection, call cloudnet-mcp APIs to list sites and run executeStaDiagnosis, and report results. The SKILL.md does not instruct reading unrelated system files or exfiltrating data beyond Cloudnet.

Install Mechanism

This is an instruction-only skill (no install spec), but it instructs installing an npm package globally (npm install -g mcporter) and installing another skill via clawhub. Global npm installs execute code on the host and can be a vector for arbitrary code; the skill provides no provenance or trusted package source information for mcporter. That raises moderate risk until the mcporter package and clawhub skill are verified.

Credentials

The only credential the skill needs is CLOUDNET_API_KEY, which is appropriate for calling the Cloudnet management APIs described. But the registry metadata inconsistency (required env vars listed as none vs SKILL.md requiring the key) is confusing. Also, a Cloudnet API key can grant wide access to network management — verify least privilege (read/diagnose only) and avoid giving full admin keys.

Persistence & Privilege

The skill does not request 'always: true' or other elevated persistence. It is user-invocable and allows normal autonomous invocation, which is expected for skills. It does instruct installing other tooling, but does not ask to modify other skills or system-wide agent configs directly.

What to consider before installing

Before installing/use: 1) Verify the mcporter npm package and the 'clawhub' skill sources and maintainers (ensure they come from trusted registries/repositories). Global npm installs run code on your machine — consider installing in a sandbox or container. 2) Clarify the metadata mismatch (skill name and required env vars) with the publisher. 3) Only provide a Cloudnet API key with minimal scope needed for diagnostics; avoid full admin keys and rotate/revoke keys after testing. 4) If you must proceed, test the workflow in an isolated environment and inspect what mcporter does (network calls, files written) before giving the skill access to production credentials.

cloudnet-analyze

针对无线场景下终端体验差、网卡、无法接入 WiFi 等问题进行排障。

触发条件

用户询问关于无线终端连接问题，例如：

• "XX 场所的 XX 终端上网很慢"
• "XX 场所的 XX 设备连不上 WiFi"
• "XX 场所的 XX 用户反馈网络卡"

前置环境检查

安装mcportercli支持及skill支持

• mcporter: npm install -g mcporter
• 然后再通过clawhub安装mcporter技能

配置MCP连接参数

• CLOUDNET_API_KEY 必须. 需要用户提供Cloudnet管理平台的API KEY，可通过Cloudnet管理平台（网络管理=>设置=>开放平台）获取
• 可选: CLOUDNET_BASE_URL Cloudnet管理平台地址. 默认使用https://oasis.h3c.com
• 执行```bash mcporter config add cloudnet-mcp ${CLOUDNET_BASE_URL}/api/sse --header Authorization="Bearer ${CLOUDNET_API_KEY}"

## 排障步骤

### 第一步：提取关键信息

从用户问题中提取以下信息：

| 信息 | 说明 | 示例 |
|------|------|------|
| **场所名** | 必填，问题发生的场所 | "总部办公室"、"XX门店" |
| **终端信息** | 必填，MAC 地址或终端用户名 | MAC: `xxxx-xxxx-xxxx` 或用户名: `zhangsan` |
| **故障时间** | 可选，用户未指定则默认当前时间 | "2026-03-24 10:00:00" |

**重要**：如果场所名和终端信息未提取到，必须让用户补充完整后才能继续下一步。

### 第二步：查询场所 ID

调用 `cloudnet-mcp.getallshopsanddevofuser` 获取用户下所有场所，找到场所名对应的场所 ID。

```bash
mcporter call cloudnet-mcp.getallshopsanddevofuser

第三步：执行终端诊断

根据提取的终端信息（MAC 或用户名），调用 executeStaDiagnosis 进行诊断：

参数说明：

• MAC: 终端 MAC 地址，格式 xxxx-xxxx-xxxx
• shopId: 场所 ID（来自第二步），需要转为字符串类型
• faultTime: 故障时间，格式 yyyy-MM-dd HH:mm:ss，用户未指定则使用当前时间
• timezone: 用户时区，默认 Asia/Shanghai

mcporter call cloudnet-mcp.executeStaDiagnosis MAC:"xxxx-xxxx-xxxx" shopId:"场所ID" faultTime:"2026-03-24 10:00:00" timezone:"Asia/Shanghai"

第四步：分析诊断结果

诊断返回后会包含：

• 终端连接状态
• 信号强度
• 接入 AP 信息
• 可能的根因
• 优化建议

结合诊断结果回答用户问题，并给出具体的解决建议。

输出格式

完成排障后，向用户清晰说明：

1. 诊断结果摘要
2. 问题根因分析
3. 建议的解决措施