by im4codes · Codex Skill · ★ 666
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IM.codes English 한국어 The IM for agents. Shared memory, managed MCP tools, supervised execution, and cross-agent audit across AI providers. Two heads are better than one. But minds in concert don't answer fate, they author it. — IM.codes IM.codes gives coding agents one shared memory layer and one managed MCP tool surface across providers. It turns completed work into reusable context, then injects or recalls the right history in future sessions across Claude Code, Codex, Gemini CLI, GitHub Copilot, Cursor, OpenCode, OpenClaw, Qwen, and more — with terminal access, file browsing, git views, localhost preview, notifications, multi-agent workflows, and native streaming output for transport-backed agents. Built-in Auto supervision can judge completed turns, continue work autonomously, and optionally run an audit/rework loop before handing control back. Team discussion lets multiple models review and audit each other's plans and implementations — an effective way to reduce single-model misses, blind spots, and biases. Di
| Stars | 666 |
| Forks | 92 |
| Language | TypeScript |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 61.5995212499761/100 |
| Last Updated | 2026-07-02 |
| Created | 2026-03-18 |
| Platforms | claude-code, cli, codex, gemini, node |
| Est. Tokens | ~21k |
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imcodes is The IM for agents. Shared Agent Context & Memory, supervised execution, and cross-agent audit across AI providers.. It is categorized as a Codex Skill with 666 GitHub stars.
imcodes is primarily written in TypeScript. It covers topics such as ai, ai-agents, automation.
You can find installation instructions and usage details in the imcodes GitHub repository at github.com/im4codes/imcodes. The project has 666 stars and 92 forks, indicating an active community.
imcodes is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to imcodes on Agent Skills Hub include pilot-shell, awesome-llm-skills, quint-code. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.