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 zhinkgit/embeddedskills --skill cangit clone --depth 1 https://github.com/zhinkgit/embeddedskillsWrote 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/zhinkgit/embeddedskills/can)<a href="https://agentmods.dev/skills/zhinkgit/embeddedskills/can"><img src="https://agentmods.dev/badge/skills/zhinkgit/embeddedskills/can/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/zhinkgit/embeddedskills/can"><img src="https://agentmods.dev/badge/skills/zhinkgit/embeddedskills/can.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00168 | $0.01861 |
| Opus 5.5 | $0.00067 | $0.00744 |
| Sonnet 5.5 | $0.00034 | $0.00372 |
| Haiku 4.5 | $0.00017 | $0.00186 |
Grade A, and why
can 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 1mo 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 — 162 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CAN — 嵌入式 CAN / CAN-FD 调试工具
统一封装接口发现、实时监控、报文发送、日志记录、数据库文件解码和统计分析能力。
配置
环境级配置 (skill/config.json)
仅保留 slcan 相关的环境级配置:
{
"slcan_serial_port": "",
"slcan_serial_baudrate": 115200
}
| 字段 | 说明 | 默认值 |
|---|---|---|
slcan_serial_port |
slcan 场景的串口 | "" |
slcan_serial_baudrate |
slcan 场景的串口速率 | 115200 |
工程级配置 (.embeddedskills/config.json)
工作区下的 .embeddedskills/config.json 存放工程级 CAN 配置:
{
"can": {
"interface": "",
"channel": "",
"bitrate": 500000,
"data_bitrate": 2000000,
"log_dir": ".embeddedskills/logs/can"
}
}
| 字段 | 说明 | 默认值 |
|---|---|---|
interface |
CAN 后端,如 pcan / vector / slcan |
"" |
channel |
通道名,如 PCAN_USBBUS1 |
"" |
bitrate |
仲裁域比特率 | 500000 |
data_bitrate |
CAN-FD 数据域比特率 | 2000000 |
log_dir |
日志输出目录 | .embeddedskills/logs/can |
参数解析优先级
- CLI 参数 (
--interface,--channel,--bitrate等) - 最高优先级 - 工程级配置 (
.embeddedskills/config.json中的can部分) - 状态文件 (
.embeddedskills/state.json中的历史记录) - 默认值 - 最低优先级
自动扫描行为
当未指定 interface 和 channel 时,脚本会自动扫描系统 CAN 接口,按以下步骤处理:
- 扫描系统中所有可用 CAN 接口
- 若只找到一个接口 → 自动使用并写入工程配置
- 若找到多个接口 → 返回候选列表,等待用户选择
- 若未找到接口 → 提示错误,停止执行
子命令
| 子命令 | 用途 | 风险 |
|---|---|---|
scan |
扫描可用 CAN 接口与 USB-CAN 设备 | 低 |
monitor |
实时监控总线报文 | 低 |
send |
发送标准帧 / 扩展帧 / 远程帧 / CAN-FD 帧 | 高 |
log |
记录总线报文到 ASC / BLF / CSV 文件 | 低 |
decode |
用 DBC 等数据库文件解码报文或日志 | 低 |
stats |
统计总线负载、ID 分布和帧率 | 低 |
执行流程
- 检查
python-can是否可用,未安装时提示pip install python-can - 按优先级解析参数:CLI > 工程级配置 > 状态文件 > 默认值
- 无子命令时默认执行
scan monitor / send / log / stats使用解析后的连接参数decode先确认数据库文件和输入源存在- 若未指定
interface/channel,自动扫描系统 CAN 接口:- 唯一候选:自动使用并写入工程配置
- 多候选:返回列表让用户选择
- 成功执行后,将确认的参数写回工程配置
send只要配置可连接就直接执行,不二次确认- 运行对应脚本并输出结构化结果
- 失败时优先反馈接口、驱动、比特率和过滤条件问题
脚本调用
所有脚本位于 skill 目录的 scripts/ 下,通过 python 直接调用。
脚本会按优先级从 CLI 参数、工程级配置、状态文件中读取参数。
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 65 B
- README.md 3.9 KB
- references/common_interfaces.json 1.6 KB
- scripts/can_decode.py 8.7 KB runs code
- scripts/can_log.py 5.6 KB runs code
- scripts/can_monitor.py 6.3 KB runs code
- scripts/can_runtime.py 15 KB runs code
- scripts/can_scan.py 7.1 KB runs code
- scripts/can_send.py 6.7 KB runs code
- scripts/can_stats.py 7.7 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.
- 1mo ago First seen · 162 lines · 168 tokens per session scan A a9716730c7bb
can is a skill published in the GitHub repository zhinkgit/embeddedskills (755 stars, last pushed 1mo ago), licensed MIT. It adds 168 tokens to every session and 1,861 once invoked, about $0.0007 per session on Opus 5.5. 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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