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 agentmods add skills/zhinkgit/embeddedskills/netnpx skills add zhinkgit/embeddedskills --skill netgit clone --depth 1 https://github.com/zhinkgit/embeddedskillsWhat 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 | $0.00234 | $0.02126 |
| Opus 5 | $0.00117 | $0.01063 |
| Sonnet 5 | $0.00047 | $0.00425 |
| Haiku 4.5 | $0.00023 | $0.00213 |
Grade A, and why
net 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 2d 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Net Debug Skill
嵌入式网络通信调试工具,统一封装接口发现、抓包、离线分析、连通性测试、端口扫描和流量统计能力。
脚本与配置路径
- 脚本目录:
<skill-dir>/scripts/ - 环境级配置:
<skill-dir>/config.json(仅工具路径) - 工程级配置:
<workspace>/.embeddedskills/config.json(网络参数) - 协议参考:
<skill-dir>/references/common_protocols.json
依赖
tshark(随 Wireshark 安装,需加入 PATH)dumpcap(随 Wireshark 安装)- 可选:
capinfos - Windows 自带:
ipconfig、ping、tracert、netstat、arp、nslookup - Python 3.x (仅标准库)
- 抓包需要 Npcap 驱动,部分环境需管理员权限
配置
环境级配置 (skill/config.json)
仅保留工具路径相关的环境级配置:
{
"tshark_exe": "tshark",
"capinfos_exe": "capinfos"
}
工程级配置 (.embeddedskills/config.json)
工作区下的 .embeddedskills/config.json 存放工程级网络配置:
{
"net": {
"interface": "",
"target": "",
"capture_filter": "",
"display_filter": "",
"duration": 30,
"timeout_ms": 1000,
"scan_ports": "",
"capture_format": "pcapng",
"log_dir": ".embeddedskills/logs/net"
}
}
参数解析优先级
- CLI 参数 (
--interface,--target等) - 最高优先级 - 工程级配置 (
.embeddedskills/config.json中的net部分) - 状态文件 (
.embeddedskills/state.json中的历史记录) - 默认值 - 最低优先级
连接和采集参数按优先级解析,脚本通过 CLI 参数接收覆盖值。若配置缺少必要项或连接失败,询问用户并引导修改配置。
执行流程
- 检查
tshark是否可用;若不可用,提示用户安装 Wireshark(含 tshark)并确认已加入 PATH;若需要抓包,还需提示安装 Npcap 驱动;依赖缺失时终止执行并输出status: error及安装指引 - 按优先级解析参数:CLI > 工程级配置 > 状态文件 > 默认值;若多个来源对同一参数均有值,以更高优先级来源为准,并在输出 summary 中注明被覆盖的来源
- 若无子命令,默认执行
iface(列出网络接口) - 成功执行后,将确认的参数写回工程配置
- 运行对应脚本并输出结构化 JSON 结果
- 失败时优先提示权限、Npcap、过滤器、接口选择等问题
子命令
iface — 列出网络接口
python <skill-dir>/scripts/net_iface.py [--filter <关键词>] [--tshark] [--json]
--tshark: 同时显示 tshark 抓包接口索引映射--filter: 按关键词筛选接口- 无副作用,可直接执行
capture — 抓包
python <skill-dir>/scripts/net_capture.py [--interface <接口>] [--duration <秒>] [--capture-filter <过滤器>] [--display-filter <过滤器>] [--output <文件路径>] [--format <pcapng|pcap>] [--decode-as <规则>] [--json]
- 接口、过滤器、时长按优先级解析
--interface: 抓包接口(覆盖配置)--duration: 抓包时长(覆盖配置)--capture-filter: BPF 抓包过滤器(覆盖配置)--display-filter: Wireshark 显示过滤器(覆盖配置)--output: 保存抓包文件路径--json: 输出 JSON Lines 格式(基于 tshark -T ek)--decode-as: 自定义解码规则- 默认格式 pcapng,参数完整后直接执行
What ships with it
10 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.
- config.example.json 59 B
- README.md 2.6 KB
- references/common_protocols.json 4.0 KB
- scripts/net_analyze.py 12 KB runs code
- scripts/net_capture.py 8.0 KB runs code
- scripts/net_iface.py 3.4 KB runs code
- scripts/net_ping.py 7.2 KB runs code
- scripts/net_runtime.py 17 KB runs code
- scripts/net_scan.py 5.6 KB runs code
- scripts/net_stats.py 8.6 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.
- 2d ago First seen · 203 lines · 234 tokens per session scan A 9fac1cce6626
net is a skill published in the GitHub repository zhinkgit/embeddedskills (610 stars, last pushed 13d ago), licensed MIT. It adds 234 tokens to every session and 2,126 once invoked, about $0.0012 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 2026-08-30.
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