Claude-to-IM-skill — What is it?

The op7418/Claude-to-IM-skill project bridges Claude Code or Codex to instant messaging platforms, enabling users to interact with AI coding agents via Telegram, Discord, Feishu/Lark, QQ, or WeChat.

⭐ 2,017 Stars 🍴 230 Forks TypeScript MIT Author: op7418
Source: Description per README View on GitHub →

Why it matters

This project is gaining attention due to its unique ability to integrate AI coding agents with popular IM platforms, addressing the pain point of limited interaction options for AI coding tools. It fills the gap by providing a seamless and interactive way to use AI coding agents in real-time communication. The project stands out for its support for multiple IM platforms and its ease of setup and use.

Source: Synthesis of README and project traits

Core Features

Multi-platform support

Supports interaction with AI coding agents across Telegram, Discord, Feishu/Lark, QQ, and WeChat, allowing users to choose their preferred IM platform.

Source: Features per README
Interactive setup

Guided wizard for collecting tokens and setting up the skill, ensuring a straightforward installation process.

Source: Features per README
Permission control

Explicit approval required for tool calls, enhancing security and user control over interactions.

Source: Features per README
Streaming preview

Real-time preview of AI responses in Telegram and Discord, enhancing the interactive experience.

Source: Features per README
Session persistence

Conversations are maintained even after daemon restarts, ensuring continuity of interaction.

Source: Features per README
Secret protection

Tokens are stored securely and auto-redacted in logs, protecting sensitive information.

Source: Features per README

Architecture

The project follows a modular architecture with distinct components for different IM platforms. It uses a background daemon to connect IM bots to Claude Code or Codex sessions, forwarding messages and receiving responses. Key technical decisions include the use of SDKs for different platforms and a focus on security and user experience.

Source: Architecture description per README and code tree

Tech Stack

infra: Not specified, but likely to be a local Node.js environment  |  key_deps: @anthropic-ai/claude-agent-sdk, claude-to-im, qrcode, @openai/codex-sdk  |  language: TypeScript  |  framework: Node.js

Source: Dependency files + code tree

Quick Start

```bash # Claude Code npx skills add op7418/Claude-to-IM-skill /claude-to-im setup # Codex bash ~/code/Claude-to-IM-skill/scripts/install-codex.sh claude-to-im setup ```
Source: README Installation/Quick Start

Use Cases

The project is suitable for developers and technical teams who need to integrate AI coding agents into their workflow for real-time code assistance, debugging, or collaboration. It is useful in scenarios where developers require immediate feedback on code changes or need to collaborate with team members across different IM platforms.

Source: README

Strengths & Limitations

Strengths

  • Strength 1: Cross-platform compatibility allows for flexible integration into various communication tools.
  • Strength 2: User-friendly setup and permission controls enhance security and ease of use.

Limitations

  • Limitation 1: Limited to text-based interactions, with no support for image or voice inputs in some platforms.
  • Limitation 2: May require additional setup for certain platforms, such as Feishu/Lark and WeChat.
Source: Synthesis of README, code structure and dependencies

Latest Release

Not enough information.

Source: GitHub Releases

Verdict

The op7418/Claude-to-IM-skill project is a valuable tool for developers seeking to enhance their coding workflow with AI assistance. Its multi-platform support and user-friendly setup make it a compelling choice for teams looking to integrate AI coding agents into their daily communication and collaboration processes.

Transparency Notice
This page is auto-generated by AI (a large language model) from the following public materials: GitHub README, code tree, dependency files and release notes. Analyzed at: 2026-04-19 10:23. Quality score: 85/100.

Data sources: README, GitHub API, dependency files