Xiaomi's MiMo Code: A Free AI Coding Assistant with Persistent Memory and Skill Distillation
Install and configure MiMo Code, a no-cost AI tool that remembers sessions and can convert your coding patterns into reusable skills.
Practical Summary
This tutorial covers installing Xiaomi's free MiMo Code tool and explains how its key features—like persistent memory, automatic subagents, and workflow distillation—can be used to create more efficient, reproducible coding workflows.
Why It Matters
For developers and teams, this tool offers a way to reduce repetitive setup time and preserve context across coding sessions without incurring API costs, potentially streamlining development cycles and improving AI-assisted productivity.
What is MiMo Code?
MiMo Code is a free, open-source AI coding assistant from Xiaomi. It includes a built-in model (MiMo Auto) that requires no API keys or configuration. Key features include persistent memory that retains context between sessions and tools to automate and save your workflows.
Installation Steps
1. For Mac or Linux, open your terminal and run the command: curl -fsSL https://mimo.xiaomi.com/install | bash
2. For Windows, run: npm install -g @mimo-ai/cli
3. After installation, start the tool by typing 'mimo' in your terminal.
Core Workflow Features Explained
Persistent Memory: The tool remembers your exact work progress from one session to the next, allowing you to stop and continue later without losing context.
Automatic Subagents: The system can spawn helper agents that run tasks in parallel, which can speed up complex operations.
/dream Command: This command extracts knowledge from your current session and saves it to the project's long-term memory, building a useful knowledge base over time.
/distill Command: Use this to capture a series of repeated actions or workflows and turn them into a single, reusable skill or macro. This is key for optimizing repetitive tasks.
/goal Command with Judge Model: This feature uses a separate model to objectively verify if a coding task is truly complete, not just if the AI thinks it is done, adding a layer of quality control.
