An open-source AI content search engine designed specifically for content creators. Supports extraction of text, images, and short videos. Allows full local deployment (web app, RAG server, LLM server). Supports multi-modal RAG content Q&A.
Creating a software for automatic monitoring in online proctoring.
Key parameters and specifications
Key parameters and specifications
Parameter
Value
Language
TypeScript
Category
Applications
Subcategory
Coding
Keywords
Coding, IDE
Stars
633
Forks
38
Contributors
10
Created date
2025-07-13
Updated date
2026-10-10
Stars in 1 day
0
Stars in 7 days
-1
Rank
15,772
Previous rank
15,572
Rank change
-200
7-day stars rank
17,808
Previous 7-day stars rank
17,762
7-day stars rank change
-46
Total stars rank
16,108
Previous total stars rank
16,080
Total stars rank change
-28
README summary
Tasksync Reduce premium AI credits cost and manage tasks seamlessly with human-in-the-loop workflows. TaskSync provides three options to integrate feedback loops into your AI-assisted development. Choose Your Option Option 1: TaskSync (VS Code Extension) - Recommended A dedicated VS Code sidebar extension with smart prompt queue system. _Setup instructions here: tasksync-chat folder. _ **Features:** Smart Queue Mode - batch responses for AI agents Autopilot - let agents work autonomously with customizable auto-responses Agent orchestration toggle - switch between multi
-session routing and a single-session lane per workspace Remote Access - control from your phone via LAN or Tailscale, with PWA and code review Give new tasks/feedback using ask_user tool File, folder, tool, and context references with autocomplete Image paste support (copilot will view your image) Tool call history with session tracking **Installation:** Install from VS Code Marketplace or build from source with . Your coding agent actively requests tasks or feedback through terminal commands, executes tasks autonomously, and
operates until you stop it. **Features:** Human-in-the-loop workflow - provide feedback or new tasks Terminal-based agent interaction Autonomous operation - runs continuously Never terminates automatically **Getting Started:** 1. Choose your preferred prompt TaskSync Prompt 2. Agent executes and waits for input For spec-driven development, use Specs-Tasksync instead. **Note:** Use (Linux/Mac) or (Windows) to signal end of input. It uses the tool to collect your input from the file in the workspace, which is sent back
to the agent when you save. Recommended settings for agent mode: **Enable "Auto Approve" in settings for uninterrupted agent operation. ** Discussions The TaskSync community can be found on GitHub Discussions where you can ask questions, voice ideas, and share your prompts with other people. Contributions to TaskSync are welcome and highly appreciated. Star History ⭐ Drop a star if you find this useful!
Frequently asked questions
How many stars and forks are recorded?
4regab/TaskSync has 633 stars and 38 forks.
What is the repository rank?
4regab/TaskSync is ranked 15,772.
What language and category are recorded?
4regab/TaskSync has 633 stars, uses TypeScript and belongs to Applications.
Which repository is closest in rank?
4regab/TaskSync is compared with abgulati/LARS, ranked 15,775 with 633 stars.
README
Tasksync
Reduce premium AI credits cost and manage tasks seamlessly with human-in-the-loop workflows. TaskSync provides three options to integrate feedback loops into your AI-assisted development.
A terminal-based task agent protocol. Your coding agent actively requests tasks or feedback through terminal commands, executes tasks autonomously, and operates until you stop it.
Features:
Human-in-the-loop workflow - provide feedback or new tasks
Agent executes python -c "import sys; sys.stdin.read()" and waits for input
For spec-driven development, use Specs-Tasksync instead.
Note: Use Ctrl+D (Linux/Mac) or Ctrl+Z + Enter (Windows) to signal end of input.
Option 3: TaskSync MCP Server
This is an MCP server that helps with feedback-oriented development workflows in AI-assisted development by letting users give feedback while the agent is working. It uses the get_feedback tool to collect your input from the feedback.md file in the workspace, which is sent back to the agent when you save.
Setup instructions: TaskSync MCP Server
Best Practices (VS Code Copilot)
For GPT models, use TaskSync Extension.
Recommended settings for agent mode:
"chat.agent.maxRequests": 999
Enable "Auto Approve" in settings for uninterrupted agent operation. Sessions beyond 2 hours may produce lower-quality results — TaskSync will warn you when it's time to consider starting a fresh session.
Discussions
The TaskSync community can be found on GitHub Discussions where you can ask questions, voice ideas, and share your prompts with other people. Contributions to TaskSync are welcome and highly appreciated.