Cherry Electron Dev logo

Cherry Electron Dev

OrganizationPopular
CherryHQ
cherry-electron-dev

Develop, fix, and profile Cherry Studio in a tracked Electron instance. Use for everyday implementation, UI and interaction work, bug fixing, runtime debugging, DevTools inspection, lag or jank investigation, CPU and memory monitoring, leak checks, and startup-performance analysis; reuse a verified workspace instance across instructions and launch or replace one only when required.

Overview

PublisherCherryHQ
Repositorycherry-studio
Skill namecherry-electron-dev
Stars
52.5K
Forks
5.1K
Bundled files
2
LicenseAGPL-3.0
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 CherryHQ on GitHub. Read the source before you install it.

Installation

Install the Cherry Electron Dev 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/CherryHQ/cherry-studio/tree/main/.agents/skills/cherry-electron-dev
  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/CherryHQ/cherry-studio.git /tmp/cherry-studio
mkdir -p .claude/skills
cp -r /tmp/cherry-studio/.agents/skills/cherry-electron-dev .claude/skills/cherry-electron-dev
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cherry Electron Dev 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 Cherry Electron Dev 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 Cherry Electron Dev 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.

Cherry Studio Development

Use this skill for ongoing work in the current checkout. Do not use it to check out or report on PRs; use cherry-pr-test for that workflow.

Required runtime workflow

Before reading or controlling Electron UI, read Electron Instance Management and use its persistent policy.

That reference is the only authority for instance discovery, instance.json, CDP target selection, launching, replacement, shutdown, and troubleshooting. Do not reproduce those procedures here or substitute generic Electron app control.

Development loop

  1. State the requested behavior and the evidence that will prove it.
  2. Read the relevant code and nearby README files.
  3. Verify and reuse the tracked instance through the runtime reference.
  4. Reproduce or inspect the current behavior before editing when practical.
  5. Capture the smallest useful evidence: UI state, DOM, console/network output, main-process logs, persisted state, or performance metrics.
  6. Trace the responsible code path and make only the requested change.
  7. Keep Electron running. Use HMR for renderer changes and verify in the same window.
  8. Repeat the same scenario and compare before/after evidence.

Inspect the real window at the relevant size and theme for UI work. Check both renderer and main-process evidence for renderer failures.

Restart only for a non-reloadable layer, crash, unreliable runtime state, or startup profiling. Use the reference's exact-instance replacement procedure, refresh instance.json, and keep the replacement running.

Run the narrowest relevant validation and follow current user and repository instructions for lint, formatting, and tests.

Performance and DevTools

For lag, jank, high CPU, memory growth, leaks, slow startup, or explicit DevTools use, read Performance Debugging.

Store temporary logs, screenshots, and profiles under .context/cherry-electron-dev/. Compare a quiet baseline with the same bounded scenario before and after a fix. Detach profiling sessions afterward; do not close the CDP browser, page, or Electron process.

Handoff

Leave reused user-owned and healthy agent-launched instances running after the instruction. Stop one only when the user asks, a required restart is part of the task, or the instance is unhealthy and blocks progress.

Report the verified PID, whether it remains running, CDP port, tracking file, evidence paths, reproduction, and verification.

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 Cherry Electron Dev AI skill do?

Develop, fix, and profile Cherry Studio in a tracked Electron instance. Use for everyday implementation, UI and interaction work, bug fixing, runtime debugging, DevTools inspection, lag or jank investigation, CPU and memory monitoring, leak checks, and startup-performance analysis; reuse a verified workspace instance across instructions and launch or replace one only when required.

Why use Cherry Electron Dev on TypingMind?

Because you install it once and use it with any model. Cherry Electron Dev 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 Cherry Electron Dev in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CherryHQ/cherry-studio/tree/main/.agents/skills/cherry-electron-dev. 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 Cherry Electron Dev?

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 Cherry Electron Dev?

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

Is the Cherry Electron Dev AI skill free?

Yes. It is published on GitHub by CherryHQ under the AGPL-3.0 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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