FutureUniant

FutureUniant / WorkShadow

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如影随形 · 本地优先桌面工作日志：富文本记录、语义检索、工作台总结/问答；模型自配，数据留在本机。 Local-first desktop work journal—rich logs, semantic search, AI summary & Q&A. BYO models, data stays yours.

agent ai rich-text-editor work
42
1
89% credibility
Found May 29, 2026 at 42 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
TypeScript
AI Summary

WorkShadow is a free, open-source desktop application that serves as a personal work journal. It combines a rich text editor for daily note-taking with powerful search capabilities, allowing users to quickly find past work by keywords or by meaning. For users who want AI assistance, it can connect to external language models to generate summaries and answer questions about accumulated logs. All data stays local on the user's computer, with optional cloud AI calls only when the user configures their own models. The app supports both Chinese and English, offers dark and light themes, and provides backup/restore functionality through .ws files.

How It Works

1
📝 You discover a personal work journal

You hear about an app that remembers everything you do at work—so you can find it later when you need it.

2
💻 You install it on your computer

You download and set up the application, which keeps all your data stored safely on your own machine—no cloud uploads.

3
✍️ You start writing your daily work logs

You open the editor and capture decisions, progress, and notes throughout your workday, building a record of what happened.

4
🔍 You search for something you wrote months ago

Instead of digging through folders, you type what you're looking for and instantly find the exact note—either by matching words or by meaning.

5
You get smart help when you want it
📊
Generate work summaries

Select several logs and let AI draft your weekly report or status update based on your writing style

💬
Ask questions about your history

Ask things like 'what happened with that project last month?' and get answers synthesized from all your notes

6
🗂️ You organize and back up everything

You keep your notes tidy in folders, and export everything as a single backup file whenever you want—so nothing is ever lost.

🌟 You have your own searchable work memory

Everything you did is captured, findable, and understandable—even to your future self who forgot the details.

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Star Growth

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AI-Generated Review

What is WorkShadow?

WorkShadow is a local-first desktop work journal built with TypeScript and Tauri. It gives you a tree-based log manager on the left and a rich text editor on the right for capturing daily work, decisions, and notes. The standout feature is semantic search powered by vector embeddings plus AI-assisted summarization and Q&A across your entire log history. You bring your own models through Settings - data never leaves your machine. It supports markdown import, image/video embedding, tables, math formulas, and exports everything to .ws backup files for portability.

Why is it gaining traction?

The privacy angle is strong: no cloud, no uploads, your logs stay on your disk while still getting AI-powered search and summaries. The semantic search is the killer feature - instead of remembering exact keywords from months ago, you describe what you were working on and the system finds relevant entries through vector similarity. The Workspace feature lets you select multiple logs and draft reports or ask questions across your entire history, with sources cited. For developers who want to track decisions and context without dumping everything into Notion or Obsidian, this fills a specific niche.

Who should use this?

Software developers maintaining decision logs, technical writers tracking documentation updates, or anyone who needs to find "that thing I worked on in March" without remembering specific keywords. QA engineers logging bug investigations would benefit from the semantic search. Teams wanting AI assistance on private project history without sending data to third-party services will find this compelling. It's less useful for casual note-taking - this is a structured work journal with opinionated workflows.

Verdict

At 42 stars, WorkShadow is early-stage and the credibility score of 0.8999999761581421% reflects that. The AGPL license and local-first architecture are refreshingly transparent, and the feature set is genuinely useful for its target use case. If you need a privacy-respecting work journal with semantic search, this is worth watching - but treat it as pre-1.0 software and test thoroughly before committing to it for critical workflows. The BYO model approach is smart positioning for developers who already pay for API access and want control over their data.

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