Baoyu Electron Extract logo

Baoyu Electron Extract

CommunityPopular
JimLiu
baoyu-electron-extract

Extracts resources and JavaScript from any installed Electron app (`.asar` bundle), restoring original sources from `.js.map` files when available or formatting minified code with Prettier otherwise. Use when user wants to "extract Electron app", "decompile Electron", "get the source code of <app>", "inspect app.asar", "看 Electron 应用源码", "提取 .asar", or asks how a desktop Electron app is built. Skips `node_modules` and supports both macOS and Windows.

Overview

PublisherJimLiu
Repositorybaoyu-skills
Skill namebaoyu-electron-extract
Stars
26K
Forks
2.9K
Bundled files
2
LicenseMIT
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Baoyu Electron Extract 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.
  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/JimLiu/baoyu-skills.git /tmp/baoyu-skills
mkdir -p .claude/skills
cp -r /tmp/baoyu-skills/skills/baoyu-electron-extract .claude/skills/baoyu-electron-extract
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Baoyu Electron Extract 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 Baoyu Electron Extract 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 Baoyu Electron Extract 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.

Electron App Extract

Extracts resources and code from an installed Electron app's app.asar. When a .js.map is present, restores the original source files from the embedded sourcesContent; otherwise formats the minified code with Prettier. Source-map paths are resolved relative to the .js.map file first, so bundled paths like ../../src/main.ts restore to readable paths such as restored/src/main.ts instead of hashed placeholders. Always skips node_modules. Works on macOS and Windows.

User Input Tools

When this skill prompts the user, follow this tool-selection rule (priority order):

  1. Prefer built-in user-input tools exposed by the current agent runtime — e.g., AskUserQuestion, request_user_input, clarify, ask_user, or any equivalent.
  2. Fallback: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question.
  3. Batching: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.

Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes.

Script Directory

Scripts in scripts/ subdirectory. {baseDir} = this SKILL.md's directory path. Resolve ${BUN_X} runtime: if bun installed → bun; if npx available → npx -y bun; else suggest installing bun. Replace {baseDir} and ${BUN_X} with actual values.

ScriptPurpose
scripts/main.tsApp discovery + asar extraction + source-map restoration + Prettier formatting

When to use

Use this skill whenever the user wants to look inside an installed Electron application or inspect its bundled code. Trigger phrases include:

  • "extract Electron app", "decompile this Electron app", "unpack app.asar"
  • "show me the source of ", "look inside ", "how is built"
  • "get the source code of Codex / Cursor / Discord / Slack / VS Code / Notion / Obsidian / ChatGPT desktop"
  • "提取 Electron 应用", "看 的源码", "反编译 Electron", "解包 app.asar", "还原 source map"

Both app name (e.g., Codex) and absolute path (e.g., /Applications/Codex.app, a .asar file, or a Windows install dir) are accepted. The script handles discovery for both platforms.

Workflow

1. Determine the input. Ask the user for the app name or path if they haven't given one. If they want a custom output directory, ask for that too.

2. Run the script.

bash
${BUN_X} {baseDir}/scripts/main.ts "<app>" [--output <dir>] [--asar <path>] [--force]

Start with --dry-run first if you're unsure whether discovery will find the right bundle — it prints the resolved paths and exits without touching the filesystem.

3. Handle the result.

  • Success → report the output paths and the counts (extracted / restored / formatted).
  • Multiple matches → the script lists candidates and exits non-zero. Show the user the candidates, ask which one to use (via AskUserQuestion or the runtime equivalent), then re-run with the chosen absolute path.
  • Existing non-empty output dir → the script refuses without --force. Ask the user whether to overwrite (--force) or pick a new --output path.
  • Unsupported platform / no match → suggest passing --asar /full/path/to/app.asar if the user knows where the bundle lives.

4. Point the user at the result. The default output dir is ~/Downloads/<AppName>-electron-extract/. The most interesting subdirectory depends on what was found:

  • restored/ exists → the original source tree was reconstructed from .js.map files; this is what to read first.
  • Only extracted/ exists (no maps) → the JS/CSS in extracted/ was Prettier-formatted in place; read from there.

Source-map path restoration

The script should preserve original source names and directory structure as much as the source map allows:

  • Resolve each sources[] entry with sourceRoot when present, then relative to the .js.map file's directory inside extracted/.
  • Collapse normal bundler-relative paths into the restored project tree. For example, .vite/main/index.js.map + ../../src/main.ts becomes restored/src/main.ts.
  • If a source path climbs above extracted/, keep the readable remaining path under restored/ instead of hashing it. For example, .vite/main/index.js.map + ../../../shared/src/lib/foo.ts becomes restored/shared/src/lib/foo.ts.
  • Strip URL/query decorations from source names, including common webpack://, file://, and ?loader suffixes.
  • Use restored/__unknown/<hash>.<ext> only when the source name is empty or cannot be reduced to a safe file path.
  • Continue skipping node_modules and webpack/runtime/* entries; these are bundler/runtime noise, not app sources.

Usage

bash
# Extract by app name (default output: ~/Downloads/Codex-electron-extract/)
${BUN_X} {baseDir}/scripts/main.ts Codex

# Extract by absolute path (works for .app bundles, install dirs, or .asar files)
${BUN_X} {baseDir}/scripts/main.ts "/Applications/Visual Studio Code.app"
${BUN_X} {baseDir}/scripts/main.ts "C:\Users\you\AppData\Local\Programs\codex"
${BUN_X} {baseDir}/scripts/main.ts --asar /Applications/Codex.app/Contents/Resources/app.asar Codex

# Custom output
${BUN_X} {baseDir}/scripts/main.ts Codex --output ~/work/codex-source

# Preview discovery without writing anything
${BUN_X} {baseDir}/scripts/main.ts Codex --dry-run

# Overwrite an existing output dir
${BUN_X} {baseDir}/scripts/main.ts Codex --force

# Machine-readable result (one JSON line on stdout)
${BUN_X} {baseDir}/scripts/main.ts Codex --json

Options

OptionShortDescriptionDefault
<app>App name or absolute path. Required unless --asar is given.
--output-oOutput directory~/Downloads/<AppName>-electron-extract
--asarOverride the resolved .asar pathauto-discovered
--force-fAllow writing into a non-empty existing output dirfalse
--skip-formatSkip Prettier formattingfalse
--skip-restoreSkip source-map restorationfalse
--no-unpackedDon't copy app.asar.unpacked/ alongsidefalse
--dry-runPrint resolved paths and exit without writingfalse
--jsonEmit one JSON-line summary on stdout (suppresses normal output)false

Output layout

~/Downloads/<AppName>-electron-extract/
├── extract-report.json          # JSON summary: counts, warnings, resolved paths
├── extracted/                   # raw asar contents (JS/CSS Prettier-formatted when no map)
│   └── ...                      # node_modules left untouched (skipped from format)
├── extracted.unpacked/          # copied from <asar>.unpacked/ if present
│   └── ...                      # native modules (.node), large assets
└── restored/                    # only present if at least one .js.map was usable
    └── <original/source/tree>   # rebuilt from sourcesContent in each .js.map

Notes

  • node_modules is always skipped — both for source-map restoration and Prettier formatting — because vendored dependencies are noise when inspecting an app.
  • Source-map restoration only works when the .js.map embeds sourcesContent. This is the common case for modern bundlers (webpack, esbuild, Vite, rollup). If a map references external .ts/.js files without embedding them, that map is skipped and the corresponding .js is Prettier-formatted instead. Skipped maps are listed in extract-report.json under warnings.
  • Readable paths over hashes — don't treat ../ segments in source-map paths as automatically unsafe. First resolve them from the map location and then sanitize the final output path so it still stays under restored/. Hash fallback is only for unusable source names.
  • App discovery searches /Applications + ~/Applications on macOS, and %LOCALAPPDATA%\Programs, %PROGRAMFILES%, %PROGRAMFILES(X86)%, %APPDATA% on Windows. If discovery finds multiple matches, the script exits and lists them — re-run with an absolute path. On Linux or other platforms, pass --asar /path/to/app.asar explicitly.
  • Safety — the script refuses to write to /, the user home directly, or the current working directory, and refuses to populate an existing non-empty output dir without --force.
  • No global installs@electron/asar and prettier are resolved on-the-fly via npx -y. First run will be slower while npx caches them.

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 Baoyu Electron Extract AI skill do?

Extracts resources and JavaScript from any installed Electron app (`.asar` bundle), restoring original sources from `.js.map` files when available or formatting minified code with Prettier otherwise. Use when user wants to "extract Electron app", "decompile Electron", "get the source code of <app>", "inspect app.asar", "看 Electron 应用源码", "提取 .asar", or asks how a desktop Electron app is built. Skips `node_modules` and supports both macOS and Windows.

Why use Baoyu Electron Extract on TypingMind?

Because you install it once and use it with any model. Baoyu Electron Extract 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 Baoyu Electron Extract in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/JimLiu/baoyu-skills/tree/main/skills/baoyu-electron-extract. 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 Baoyu Electron Extract?

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 Baoyu Electron Extract?

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

Is the Baoyu Electron Extract AI skill free?

Yes. It is published on GitHub by JimLiu under the MIT license. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇