Summary
This is an orchestration layer for embedded development that discovers projects in your workspace, picks build/flash/debug/observe backends, and chains them together through shared state files. Instead of reimplementing toolchain logic, it delegates to underlying skills like Keil, JLink, OpenOCD, or probe-rs based on what it finds or what you've configured. The decision tree is sensible: CLI args override config file preferences, which override auto-discovery. When it spots multiple candidates it hands you a list rather than guessing. Useful if you're juggling different embedded toolchains and want one command to handle build-flash-debug sequences without manually wiring up each step every time.
Install to Claude Code
npx -y skills add zhinkgit/embeddedskills --skill workflow --agent claude-codeInstalls into .claude/skills of the current project.
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Files
SKILL.mdView on GitHub
Workflow 编排层
本 skill 不重复实现底层逻辑，只做发现、选择、串联和聚合。
支持 Keil / GCC / EIDE 三种构建后端，以及 jlink / openocd / probe-rs 三种 flash/debug/observe 后端。
observe 阶段当前会给出 jlink:rtt、jlink:swo、openocd:semihosting、openocd:itm、probe-rs:rtt 这几类候选观测后端。
命令
python <skill-dir>/scripts/workflow_plan.py --json
python <skill-dir>/scripts/workflow_run.py plan --json
python <skill-dir>/scripts/workflow_run.py build --json
python <skill-dir>/scripts/workflow_run.py build-flash --json
python <skill-dir>/scripts/workflow_run.py build-debug --json
python <skill-dir>/scripts/workflow_run.py observe --json
python <skill-dir>/scripts/workflow_run.py diagnose --json
配置说明
workflow 不再维护独立的工程配置结构，所有工程参数统一从 .embeddedskills/config.json 读取。
配置结构
.embeddedskills/config.json 中的 workflow 段仅包含首选后端配置：
{
"workflow": {
"preferred_build": "auto",
"preferred_flash": "auto",
"preferred_debug": "auto",
"preferred_observe": "auto"
}
}
workflow 通过读取 .embeddedskills/config.json 中其他 skill 的配置段来获取工程参数（如 keil.project、eide.project、eide.config、jlink.device、probe-rs.chip 等）。
参数解析顺序
按以下决策树依次判断，命中即停止：
-
CLI 参数（优先级最高）
- 条件：用户在命令行传入
--build-backend、--flash-backend等参数 - 示例：
workflow_run.py build-flash --build-backend=keil --flash-backend=jlink --build-backend可选值：auto/keil/gcc/eide- 行为：直接使用该参数指定的后端，跳过后续步骤
- 条件：用户在命令行传入
-
配置文件（次优先）
- 条件：CLI 未指定，且
.embeddedskills/config.json的workflow段中对应preferred_*字段不为"auto" - 示例：
"preferred_build": "keil"→ 使用 keil 作为构建后端 - 行为：读取配置值并使用，跳过自动发现
- 条件：CLI 未指定，且
-
自动发现（兜底）
- 条件：CLI 未指定，且配置中
preferred_*为"auto"或字段缺失 - 示例：
"preferred_flash": "auto"→ 扫描 workspace 自动推断可用 flash 后端 - 行为：枚举候选后端列表；若唯一则直接使用，若多个则返回列表请用户确认
- 条件：CLI 未指定，且配置中
成功执行后，实际使用的后端会自动写回 .embeddedskills/config.json 的 workflow 段。
规则
- 发现多个工程或多个候选后端时，只返回候选列表，不自动猜测
- 构建、烧录、调试、观测之间优先通过
.embeddedskills/state.json串联 observe只生成推荐命令，不在 workflow 内直接长时间占用观测通道- 失败时优先返回哪个阶段失败，以及底层脚本的结构化错误
- workflow 与其他 Skill 的协同只通过
.embeddedskills/config.json、.embeddedskills/state.json和子进程调用底层 Skill
Featured
Keep your Mac awake while Claude Code and 40+ AI agents run. Sleeps when they're idle.
One time payment $9 →Integrate web data into your AI product. One API to scrape website & brand data.
Get API Key Now →Agent, run crypto. Access onchain data & trade routes via 1inch.
Install now →On Capafy, your Skill runs online 24/7 as an agent product, and you get paid every time someone uses it.
Start earning →
