Sgc Electron Delta Updater

Organization

lovstudio

sgc-electron-delta-updater

为 Electron 桌面应用设计、实现和验证增量自动更新，覆盖 macOS Sparkle、签名、appcast、发布产物与失败拦截。用户提到增量更新、Sparkle、检查更新、appcast、DMG 更新或 delta updater 时使用。

Overview

Publisher	lovstudio
Repository	`skills`
Skill name	`sgc-electron-delta-updater`
Stars	67
Forks	17
Bundled files	4
License	MIT
Links	Skill source Repository Homepage

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.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by lovstudio on GitHub. Read the source before you install it.

Installation

Install the Sgc Electron Delta Updater AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/lovstudio/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/electron-delta-updater .claude/skills/sgc-electron-delta-updater

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sgc Electron Delta Updater 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 Sgc Electron Delta Updater 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 Sgc Electron Delta Updater 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 增量更新 · Electron Delta Updates

为现有 Electron 应用交付可验证的增量更新链路；以用户实际安装包、公开更新源和安装结果为准，而不是以 CI 成功为准。

Triggers

Activate when

用户说“给这个 Electron App 加增量自动更新”或“检查更新一直转圈”。
用户提到 macOS Sparkle、appcast、DMG、blockmap、签名、公证或 delta 更新包。
User asks to “add a delta updater”, “ship Sparkle updates”, or “verify an Electron update release”.

Do not activate when

用户只想修改版本号、更新日志或普通下载页；使用版本管理或发布工作流。
用户要做网页热更新、PWA 缓存更新或移动端 OTA；使用相应平台的更新机制。

Workflow (MANDATORY)

You MUST follow these steps in order.

Step 0: Establish the update contract

Identify target platforms, package format, current updater library, update feed, signing owner, release channel, and rollback expectation.
Treat macOS delta-only behavior as an explicit product promise only when complete archives are intentionally excluded.
Separate four states: check, download/stage, install handoff, and post-restart verification.
Read references/electron-macos-delta.md for macOS Sparkle work and references/release-verification.md before modifying a release pipeline.

Step 1: Make checks bounded and recoverable

Use one in-flight check per update service.
Pass an AbortSignal through every network layer, including appcast fetches.
On timeout, abort the request, wait for stale updater state and connections to settle, then allow a later retry.
Configure the updater's own network session; do not assume it inherits a developer shell proxy.
Keep the UI state retryable after every timeout, download failure, or malformed feed.

Step 2: Enforce the artifact policy

Generate architecture-specific feed entries and match each delta to its source and target version.
Verify signature, length, architecture, and URL before staging an update.
In delta-only mode, stop on any complete-package fallback; surface a manual-install path instead of silently downloading a larger archive.
If a local feed proxy is required, bind it to loopback, permit only the verified delta URL, preserve HTTP range behavior, and keep the served artifact URL ending in .delta.

Step 3: Coordinate install and restart

Complete application cleanup before giving control to the native updater.
Keep the process alive until asynchronous install handoff is confirmed.
Use references/release-verification.md to verify the staged update and the installed version after relaunch.
For a normal user-invoked app restart without an update, use sgc-electron-app-relaunch instead.

Step 4: Validate the deliverable

Add tests for single-flight checks, timeout abort, stale-check recovery, rejected full fallback, feed proxy ranges, and asynchronous install handoff.
Run the project's format, lint, typecheck, test, package, signing, and notarization checks that apply.
Verify the public release page plus direct appcast and delta asset responses; compare the final artifact's version, digest, size, signature, and notarization state.
Report the updater backend, supported platforms, checked URLs, installed-version proof, and any manual-install condition.

Dependencies

An Electron project with a defined packaging and signing owner.
Sparkle tooling only for macOS Sparkle paths.

通用反馈闭环

用户在 Skill 驱动任务中提出修改意见时，继续当前产物前必须执行：

先判断意见是 task-specific（仅本次）还是 reusable（可跨任务复用）。
task-specific 只修改当前任务，不改 Skill。
reusable 先确定作用域：领域规则先更新对应 canonical Skill；适用于所有 Skill 的规则先更新共享规范。
完成规则更新、版本、lint 与分发核验后，再把修改应用到当前任务。
reusable 修改会使此前的“确认”“继续”“发吧”失效；完成当前产物修改和回读后必须停下，等待用户下一步指示，不自动进入发布、提交或其他外部写入。

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 Sgc Electron Delta Updater AI skill do?

Why use Sgc Electron Delta Updater on TypingMind?

Because you install it once and use it with any model. Sgc Electron Delta Updater 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 Sgc Electron Delta Updater in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lovstudio/skills/tree/main/skills/electron-delta-updater. 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 Sgc Electron Delta Updater?

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 Sgc Electron Delta Updater?

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

Is the Sgc Electron Delta Updater AI skill free?

Yes. It is published on GitHub by lovstudio 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.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Electron 增量更新 · Electron Delta Updates

Triggers

Activate when

Do not activate when

Workflow (MANDATORY)

Step 0: Establish the update contract

Step 1: Make checks bounded and recoverable

Step 2: Enforce the artifact policy

Step 3: Coordinate install and restart

Step 4: Validate the deliverable

Dependencies

通用反馈闭环

Bundled files

Frequently asked questions

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