XCoding

🥈Silver

XCoding: a lightweight AI vibe coding IDE that supports parallel multi-agent collaboration (Codex/Claude Code) and parallel multi-project development, featuring a VS Code - like editor and terminal with task-driven workflows and code change management.

5890Updated 2w ago

Intermediate30min to implementautomation

Saves ~240 min per use

Quick InstallView Source

git clone https://github.com/XCodingLab/XCoding.git

Works with:

Claude

Overview

About This Skill

How to Use

[{"step":"Define the task and scope. Open XCoding and create a new project workspace or load an existing one. Use the prompt template to specify the task (e.g., 'Refactor the authentication module for SecurePay'). Break the task into subtasks (e.g., backend logic, frontend integration, testing) and assign agents to each subtask using the multi-agent collaboration feature.","tip":"Use specific frameworks/languages in the prompt to ensure agents generate relevant code. For example, specify 'using Flask and React' to avoid generic code snippets."},{"step":"Execute the workflow. XCoding will automatically split the task and assign agents. Use the VS Code-like editor to monitor real-time code changes. Review and approve changes as they are generated. Use the terminal to run tests, linting, or deployment commands (e.g., 'pytest', 'npm test', 'docker-compose up').","tip":"Enable the 'auto-save' feature in the editor to ensure changes are synced across all agents and projects. Use the 'diff view' to compare changes before approving."},{"step":"Validate and iterate. Once the agents complete their tasks, review the generated code and test results. Use the terminal to run additional tests or manual validation (e.g., 'curl' commands to test API endpoints). Iterate on the changes by providing feedback to the agents or assigning new subtasks.","tip":"Use the 'performance metrics' feature in XCoding to compare the impact of changes (e.g., response time, memory usage). Share these metrics with your team for review."},{"step":"Finalize and document. Once the task is complete, use XCoding to generate a summary of changes, test results, and next steps. Export the summary as a markdown file or share it directly with your team via the built-in collaboration tools.","tip":"Use the 'code change management' feature to track all modifications and revert changes if needed. Tag the final version of the code for deployment."}]

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/XCodingLab/XCoding

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Use XCoding to [ACTION: e.g., 'refactor the authentication module of the [PROJECT_NAME] repository', 'implement a new API endpoint for [FEATURE_DESCRIPTION]', or 'debug and optimize the [MODULE_NAME] class']. Follow the parallel multi-agent collaboration workflow: split tasks into subtasks, assign agents to each subtask (e.g., one for backend logic, one for frontend integration, one for testing), and use the VS Code-like editor to review code changes in real-time. Ensure all changes are synced across the multi-project workspace and generate a summary of the changes made, including test results and performance improvements. Use [SPECIFIC_FRAMEWORKS/LANGUAGES] where applicable.

Example Output

### XCoding Session Summary: Refactoring Authentication Module for 'SecurePay' Project

**Agents Assigned:**
- Agent A (Backend Logic): Focused on refactoring the JWT token generation and validation logic in `auth.py`. Updated the `generate_token()` function to use a more secure algorithm (HS256 → RS256) and reduced token expiration time from 24h to 1h for better security posture. Added rate-limiting to the `/login` endpoint to prevent brute-force attacks. Wrote unit tests in `tests/test_auth.py` covering edge cases for token generation and validation.
- Agent B (Frontend Integration): Updated the React frontend (`src/components/Login.js`) to handle the new token expiration logic. Added a token refresh mechanism using the `/refresh` endpoint and improved error handling for expired tokens. Updated the UI to display a countdown timer for token expiration.
- Agent C (Testing & Optimization): Ran load tests on the updated authentication flow using Locust. Results showed a 30% reduction in response time for token generation and validation. Identified and fixed a memory leak in the Redis cache used for token storage. Updated the `docker-compose.yml` to include Redis with persistent storage.

**Code Changes Summary:**
- **Backend:** Modified `auth.py` (lines 45-120) to use RS256 tokens and added rate-limiting. Updated `requirements.txt` to include `redis>=4.5.5` and `flask-limiter>=3.3.0`.
- **Frontend:** Updated `Login.js` to handle token refresh and added a countdown timer component. Updated `package.json` to include `axios>=1.6.0` for better HTTP request handling.
- **Infrastructure:** Added Redis service to `docker-compose.yml` with 1GB memory limit and persistent volume.

**Test Results:**
- Unit Tests: 100% pass rate (24/24 tests).
- Load Tests: 1000 concurrent users, 95th percentile response time improved from 450ms to 310ms.
- Security Scan: No critical vulnerabilities detected (SonarQube scan).

**Next Steps:**
1. Merge the changes into the `dev` branch and deploy to staging for further testing.
2. Update the API documentation in Swagger to reflect the new token expiration logic.
3. Schedule a team review to discuss the changes and gather feedback.

**Files Modified:**
- `backend/auth.py` (120 lines changed)
- `frontend/src/components/Login.js` (85 lines changed)
- `docker-compose.yml` (15 lines added)
- `tests/test_auth.py` (40 lines added)

**Performance Impact:**
- Token generation time reduced by 40% (120ms → 72ms).
- Memory usage per request reduced by 15% (2.1MB → 1.8MB).

All changes were reviewed and approved by the multi-agent team using the VS Code-like editor in XCoding. The terminal was used to run tests and deploy the changes to a staging environment for validation.