Develop Screenpipe Windows

OrganizationPopular

screenpipe

develop-screenpipe-windows

Develop and test Screenpipe Windows-native changes on a disposable Azure VM created from the prepared Screenpipe Windows dev image. Use for Windows compiler, process, service, local API, desktop, capture, installer, or permission behavior. Do not use for React-only work proved by the browser mock.

Overview

Publisher	screenpipe
Repository	`screenpipe`
Skill name	`develop-screenpipe-windows`
Stars	21.9K
Forks	2.2K
Bundled files	1
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.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by screenpipe on GitHub. Read the source before you install it.

Installation

Install the Develop Screenpipe Windows 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.
https://github.com/screenpipe/screenpipe/tree/main/.claude/skills/develop-screenpipe-windows
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/screenpipe/screenpipe/tree/main/.claude/skills/develop-screenpipe-windows

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/screenpipe/screenpipe.git /tmp/screenpipe
mkdir -p .claude/skills
cp -r /tmp/screenpipe/.claude/skills/develop-screenpipe-windows .claude/skills/develop-screenpipe-windows

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

Use it in TypingMind

Enable Develop Screenpipe Windows 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 Develop Screenpipe Windows 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 Develop Screenpipe Windows 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.

Develop Screenpipe on Windows

Use a disposable VM created from the validated Screenpipe Windows dev image for all Windows-native work. The image includes the desktop, Codex, build toolchain, native caches, and evidence tooling. Read references/dev-image.md completely before creating, updating, or using the image.

The disposable VM owns the entire task after one dispatch: Codex execution, native validation, its interactive console desktop, video recording, durable evidence upload, branch push, PR creation and update, credential cleanup, and shutdown. The dispatching computer may disconnect or power off immediately. There is no inbound RDP rule, operator desktop session, or host-held agent. Do not cross-compile and present that as Windows evidence.

Never develop or test on the live release builder, and never clone it as a per-task fallback. If no validated dev image exists, stop and report that the one-time image build is required.

Shared workflow

Record the exact source worktree, base SHA, acceptance invariant, forbidden actions, and cleanup target. Preserve unrelated user changes.
Dispatch an immutable validated image version with one immutable task blob. Its runtime managed identity may read only the required Key Vault secrets and private task/evidence blobs. Never copy host credentials into it.
Let the VM fetch and verify the exact requested Git revision. Do not retain a controller process or connect an operator desktop after dispatch.
Use only repository-supported native commands. For src-tauri, run bun run test:tauri <one-filter> -- --nocapture; never raw Cargo or Tauri.
Test observable behavior, including every branch of the product invariant, rather than merely proving compilation or matching source text.
Record the VM-owned console desktop and upload durable logs, native exit code, video, and exact tested SHA before delivery.
When delivery is authorized, the VM pushes the branch, creates the PR, and updates its body with the durable video link and tested SHA.
The VM clears runtime credentials and shuts itself down even after failure. Delete the exact disposable resources later; keep the immutable image.

This workflow never authorizes publishing an app release, tag, updater metadata, or release pointer.

Bundled files

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

references/dev-image.md6 KB

Frequently asked questions

What does the Develop Screenpipe Windows AI skill do?

Why use Develop Screenpipe Windows on TypingMind?

Because you install it once and use it with any model. Develop Screenpipe Windows 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 Develop Screenpipe Windows in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/screenpipe/screenpipe/tree/main/.claude/skills/develop-screenpipe-windows. 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 Develop Screenpipe Windows?

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 Develop Screenpipe Windows?

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

Is the Develop Screenpipe Windows AI skill free?

It is published on GitHub by screenpipe. 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Develop Screenpipe on Windows

Shared workflow

Bundled files

Frequently asked questions

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