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Flash Idf

Community
LeoKemp223
flash-idf

当需要通过 ESP-IDF 工具链烧录固件到 ESP32 系列芯片,或启动调试会话时使用。

Overview

PublisherLeoKemp223
Repositoryembed-ai-tool
Skill nameflash-idf
Stars
995
Forks
168
Bundled files
3
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by LeoKemp223 on GitHub. Read the source before you install it.

Installation

Install the Flash Idf AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/LeoKemp223/embed-ai-tool/tree/master/skills/flash-idf
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LeoKemp223/embed-ai-tool.git /tmp/embed-ai-tool
mkdir -p .claude/skills
cp -r /tmp/embed-ai-tool/skills/flash-idf .claude/skills/flash-idf
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Flash Idf in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Flash Idf on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Flash Idf is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ESP-IDF 烧录调试

适用场景

  • 工作区已经具备 ESP-IDF 构建产物,且用户希望烧录到目标板。
  • 用户需要擦除 Flash 或重新烧录固件。
  • 用户需要通过 JTAG 启动 OpenOCD 调试会话。
  • 团队需要一条标准化的 ESP-IDF 烧录流程,并可顺畅交接到串口监视或调试。

必要输入

  • 工作区路径(含已构建的 build/ 目录),或包含 artifact_path 的 Project Profile。
  • 串口设备路径和波特率。
  • 可选的调试探针配置(用于 JTAG 调试模式)。

首次参数确认

首次调用时,必须向用户确认以下参数,不得跳过或自动使用探测值:

  • 串口设备:列出探测到的串口设备供用户选择,即使只有一个也不得自动选择。
  • 波特率:向用户展示默认值 460800 并确认是否需要修改。

当 Project Profile 中已记录过上述参数(即非首次),可直接复用,无需再次询问。

自动探测

  • 脚本启动即自动复用工程根目录 .em_skill.json 中上次成功的 profile 作为默认参数(显式参数优先,无需先手动传 --resume);--resume 仅用于断言缓存必须存在,无缓存则非零退出。无缓存或用户明确要求重新探测时,脚本自动回退到正常扫描。
  • 扫描系统串口设备:Linux /dev/ttyUSB*、/dev/ttyACM*,macOS /dev/cu.usbserial*、/dev/cu.wchusbserial*,Windows COM*。
  • 读取 sdkconfig 中的 Flash 大小和分区表配置。
  • 检查 build/ 目录中是否存在有效的烧录产物(*.bin、flasher_args.json)。
  • 探测结果仅作为候选列表展示给用户,不自动选择。

执行步骤

  1. 先阅读 references/usage.md,确认本次是环境探测、烧录、擦除,还是启动调试。
  2. 若不确定环境状态,先运行自带脚本 scripts/idf_flasher.py 的 --detect 模式确认。
  3. 使用 --flash --project <path> 执行烧录,可通过 --port 和 --baud 指定串口参数。
  4. 若用户需要擦除 Flash,使用 --erase-flash。
  5. 若用户需要烧录后立即查看串口输出,提示手动运行 idf.py flash monitor(交互式长运行命令)。
  6. 若用户需要 JTAG 调试,使用 --debug 检测并启动 OpenOCD 服务。
  7. 读取脚本输出的烧录结果报告,重点关注烧录状态和失败分类。
  8. 将烧录配置和结果写回 Project Profile。

失败分流

  • 当 idf.py 不可用时,返回 environment-missing,提示用户安装 ESP-IDF 并激活环境(v5.x 使用 export.sh,v6.0+ 使用 EIM 激活脚本)。
  • 当串口设备不存在或被占用时,返回 connection-failure。
  • 当 Linux 用户无串口访问权限时,返回 permission-problem,建议添加 dialout 组。
  • 当 build/ 目录不存在或产物缺失时,返回 artifact-missing,推荐 build-idf。
  • 当烧录过程中芯片无响应时,返回 target-response-abnormal。
  • 当存在多个串口设备且无法确定目标时,返回 ambiguous-context。

平台说明

  • 串口设备命名因平台而异:Linux /dev/ttyUSB0,macOS /dev/cu.usbserial-*,Windows COM3。
  • Linux 用户可能需要将自己添加到 dialout 组:sudo usermod -aG dialout $USER。
  • ESP32 系列通常使用 USB-UART 桥接芯片(CP2102、CH340),需要安装对应驱动。
  • 自带脚本通过 subprocess 调用 idf.py,烧录调度路径本身是跨平台的。

输出约定

  • 输出烧录命令、串口设备、波特率、Flash 大小和烧录状态。
  • 在 Project Profile 中保留或更新 serial_port、baud_rate、idf_target。
  • 根据用户意图推荐下一步 skill:查看运行日志推荐 serial-monitor,需要调试推荐 debug-gdb-openocd。

交接关系

  • 当下一步要看运行日志时,将成功烧录结果交给 serial-monitor。
  • 当用户需要断点调试或崩溃分析时,将结果交给 debug-gdb-openocd。
  • 当固件产物缺失时,推荐用户先使用 build-idf 编译。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Flash Idf AI skill do?

当需要通过 ESP-IDF 工具链烧录固件到 ESP32 系列芯片,或启动调试会话时使用。

Why use Flash Idf on TypingMind?

Because you install it once and use it with any model. Flash Idf is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Flash Idf in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LeoKemp223/embed-ai-tool/tree/master/skills/flash-idf. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Flash Idf?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Flash Idf?

As many as you like. As long as a model supports skills, you can use Flash Idf with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Flash Idf AI skill free?

It is published on GitHub by LeoKemp223. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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