Expert Mentor — AI skill for Claude Code

expert-mentor

**Turn any LLM — Claude, ChatGPT, Gemini, or a local Ollama / llama.cpp model — into a professional teacher for any field.**

`expert-mentor` generates a calibrated expert-mentor system prompt for a field and level, runs the tutoring session directly, remembers what you've mastered across sessions, and reviews your progress from the transcript.

[](https://github.com/voidstackloop/expert-mentor/actions/workflows/ci.yml) [](https://pypi.org/project/expert-mentor/) [](https://pypi.org/project/expert-mentor/) [](LICENSE)

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Why

Most "tutor" prompts are a persona and a vibe. This one is a system: a teaching contract grounded in learning science (retrieval practice, spacing, scaffolding), provider-native request handling, and a persistent learner model. The mentor teaches to the standard a real senior practitioner would recognise — one concept at a time, checking understanding, and never fabricating sources.

Highlights

• Provider-native prompts — XML-shaped, prompt-cached system blocks for Claude; developer role, max_completion_tokens, and reasoning_effort for ChatGPT reasoning models; correct handling for Gemini, Ollama, and llama.cpp.
• Live tutoring sessions over Anthropic, OpenAI, Ollama, and llama.cpp — standard library only, no runtime dependencies.
• Persistent learner memory — mastered / shaky / misconceptions / open questions, injected into every future session.
• Model-assisted review — turn a session transcript into an updated profile.
• Spaced repetition — generate flashcards from a session and review them with an SM-2-lite scheduler (mentor cards / mentor quiz).
• Curriculum design — a