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    Expert Mentor

    2

    Turns any LLM into an expert mentor that teaches like a real pro, remembers your progress, and quizzes you until it sticks.

    Free

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    expert-mentor

    Example session with this skill installed

    I know C already, pointers and structs, want to learn modern C++ for a small game engine hobby project.

    • Read your context and instructions
    • Compiled the expert-mentor

    Turn 1

    You

    I know C already, pointers and structs, want to learn modern C++ for a small game engine hobby project.

    Mentor — Prof. Idris Ibrahim

    Welcome. It is a pleasure to meet you.

    Coming from C gives you a tremendous head start: you already understand memory layout, pointers, and the cost of indirection. That said, C++ is not merely "C with classes." In fact, your biggest challenge will likely be unlearning several manual C habits in favor of modern C++ idiom — letting the type system and lifetime rules do the heavy lifting for you so your game engine doesn't become a swamp of manual memory tracking and silent bugs.

    Before we chart our path toward your engine, three quick questions to calibrate our starting point:

    Diagnostic — In your C work, when you allocate a dynamic array or manage a resource (like a file handle or a texture), how do you typically ensure it gets cleaned up safely? Have you ever encountered

    RAII (Resource Acquisition Is Initialization)?
    2.

    Scope — What kind of engine are you planning to build (a simple 2D engine with SDL, a software rasterizer, a 3D OpenGL/Vulkan engine, or primarily a core system like an Entity Component System)?
    3. Pace — Roughly how many hours a week do you plan to invest in writing code and discussing it here?

    Tell me about these three, and we will map out a concrete syllabus.


    Turn 2

    You

    Can you explain what a smart pointer is compared to a raw pointer, with a tiny example?

    Mentor

    In C, a pointer is just an integer holding a memory address. It has no brain: it does not know if it owns the memory, how large the allocation is, or when it should be freed.

    A

    smart pointer in modern C++ is a small object (usually a lightweight struct/class template) that wraps that raw address. It behaves syntactically like a pointer — you can still use *p and p-> — but it has an automated destructor. When the smart pointer leaves its scope (such as hitting a return statement or the closing curly brace }), it automatically frees the memory it points to.

    The C / raw pointer way

    void run_c_style() {
        int* data = (int*)malloc(sizeof(int));
        *data = 42;
    
        if (some_error_condition()) {
            // Danger: if you exit early here and forget to free,
            // you have leaked memory.
            return;
        }
    
        free(data); // must manually remember this every time
    }
    

    The modern C++ way (std::unique_ptr)

    #include <memory>
    
    void run_modern_cpp() {
        // Allocates an int on the heap and wraps it in a smart pointer:
        std::unique_ptr<int> data = std::make_unique<int>(42);
    
        if (some_error_condition()) {
            return; // Safe! 'data' falls out of scope, memory is freed automatically.
        }
    
        // No free() or delete!
        // When the function ends, 'data' goes out of scope and frees the memory.
    }
    

    Notice what is missing in the second example: there is no manual cleanup call.

    Check your understanding

    If data is allocated inside an if block:

    {
        std::unique_ptr<int> data = std::make_unique<int>(100);
    }
    // <-- Right here
    

    In your own words — what happens to that heap memory the exact moment execution passes that closing brace }?

    Connects securely to your tools. The creator never sees your data.

    About this skill

    Most “AI tutor” prompts are a persona and a vibe. Ask a generic chatbot to teach you something and you get a friendly tone with none of the substance — no check for understanding, no memory of what you covered yesterday, and a real risk it just makes something up with total confidence.

    expert-mentor is different because it isn’t a persona, it’s a teaching system. Every session runs on a contract built from actual learning science — retrieval practice, spaced repetition, scaffolding — the same principles behind how real senior practitioners train juniors. The mentor doesn’t lecture at you. It checks you understood the last concept before it gives you the next one, and it’s explicitly instructed to flag uncertainty instead of fabricating a source, a formula, or an API.

    Here’s the part most tutor prompts can’t do at all: it remembers. Run a session today, close your laptop, come back next week — the mentor still knows what you’ve mastered, what’s still shaky, and what you got wrong last time. Nothing to re-explain, no starting over. Left unreviewed, most of what you “learned” this week is gone within days; expert-mentor’s SM-2-lite flashcard scheduler exists specifically to catch that before it happens.

    What you actually get

    A calibrated mentor persona for any field — “quantum computing,” “contract law,” “Rust,” whatever you need, at beginner through expert level Live tutoring sessions, run directly, against Claude, ChatGPT, Gemini, or a fully offline local model (Ollama / llama.cpp) — your choice, your data stays where you put it A persistent learner profile that tracks mastered topics, shaky ones, misconceptions, and open questions across every session Automatic post-session review that updates that profile for you — no manual bookkeeping Spaced-repetition flashcards generated straight from your transcripts A full multi-week curriculum generator when you want a structured plan instead of an open-ended chat Provider-native prompt engineering under the hood: XML-shaped, cached system blocks for Claude; correct developer-role handling for ChatGPT reasoning models; proper treatment for Gemini and local runtimes — so quality doesn’t degrade depending on which model you point it at

    Getting it running — pick your OS

    macOS / Linux/ Wsl : git clone https://github.com/voidstackloop/expert-mentor && cd expert-mentor && ./install.sh — one command, puts mentor on your PATH and links the skill into Claude Code / opencode automatically.

    It runs on the Python standard library with zero runtime dependencies, and ships with a CI suite that runs its self-tests on every single commit — so what you install is what was actually tested, not a one-off gist someone stopped maintaining.

    How to use

    Skills on Agensi run inside your AI agent. Copy the prompt, paste it into your agent, and it connects to Agensi and installs this skill for you. If a payment is needed, your agent shows it to you first.

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