npx skills add majiayu000/claude-skill-registry --skill mistral --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Mistral Mistral AI focuses on **efficiency** and **coding** capabilities. Their "Mixture of Experts" (MoE) architecture (Mixtral) changed the game. ## When to Use - **Coding**: Mistral Large 2 (Codestral) is specifically optimized for code generation. - **Efficiency**: Mixtral 8x7B offers GPT-3.5+ performance at a fraction of the inference cost. - **Open Weights**: Apache 2.0 licenses (for smaller models). ## Core Concepts ### MoE (Mixture of Experts) Only a subset of parameters (experts) are active per token. High quality, low compute. ### Codestral A model trained specifically on 80+ programming languages. ### Le Chat Mistral's chat interface (`chat.mistral.ai`). ## Best Practices (2025) **Do**: - **Use `codestral-mamba`**: For infinite context window coding tasks (linear time complexity). - **Deploy via vLLM**: Mistral models run exceptionally well on vLLM. **Don't**: - **Don't ignore small models**: Mistral NeMo (12B) is surprisingly capable for RAG. ## References - [Mistral AI Documentation](https://docs.mistral.ai/)
- When to Use
- Core Concepts
- MoE (Mixture of Experts)
- Codestral
- Le Chat
- Best Practices (2025)
- References
What does the mistral skill do?
Mistral AI efficient open models. Use for efficient AI.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill mistral --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.