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© 2025 AI студия Владимира Ломтева

Политика конфиденциальностиСогласие на обработку ПДн|ИНН 623412173261
    Self Learning — Скилл для ИИ-агентов | AI Рассвет

    Self Learning

    Autonomous skill generator that learns new technologies from the web. Use when, users want to learn about a new library/framework/tool, need to create a skill for an unfamiliar technology, want to research and document a technology's usage patterns, or invoke with /learn <topic . This skill uses web search and browser tools to discover, extract, and synthesize documentation into a reusable skill.

    Скиллы для операций#GitHub#philschmid/self-learning-skill#skills.sh
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    Установить скилл

    Добавьте инструмент одной командой или скачайте проверенный архив версии.

    npx skills add philschmid/self-learning-skill --skill self-learning
    Скачать ZIP
    Версия
    1.0.0+09474fa110e8
    Автор
    Владимир Ломтев
    Репозиторий
    philschmid/self-learning-skill
    GitHub: philschmid/self-learning-skill

    Как установить

    1. 1Скопируйте команду из блока установки.
    2. 2Запустите её в терминале из каталога проекта.

    Документация

    Self-Learning Skill Generator

    Autonomously research and learn new technologies from the web, then generate a reusable skill.

    Usage

    /learn <topic>
    

    If <topic> is missing, show usage. If topic is ambiguous, ask to clarify:

    • "react" → "React for web, React Native, or a specific library like react-query?"
    • "apollo" → "Apollo GraphQL client, Apollo Server, or Apollo Federation?"
    • "aws" → "Which AWS service? (S3, Lambda, DynamoDB, etc.)"

    Normalize to kebab-case for filenames.

    2. Discover Sources (Web Search)

    Use web search tool to find authoritative documentation:

    Search queries to try:

    1. <topic> official documentation
    2. <topic> getting started guide
    3. <topic> API reference
    4. <topic> GitHub repository

    Source prioritization:

    1. Official docs sites (e.g., docs.*, *.dev)
    2. Official GitHub repositories (README, /docs)
    3. Official blogs/announcements

    Select 3–5 high-quality URLs maximum.

    If no credible sources found, ask user to provide a URL.


    3. Extract Content (URL Reading)

    For each selected URL, read the content:

    Extract only relevant sections:

    • Installation / setup
    • Core concepts
    • API reference / key functions
    • Common patterns / examples
    • Version information

    Skip irrelevant content:

    • Navigation, ads, login prompts
    • Unrelated sidebar content
    • Comments, forums

    If reading the content fails (JavaScript-heavy sites), fall back to browser agent:

    Task: Navigate to <URL> and extract the main content including:
    - Installation instructions
    - Core concepts and API reference
    - Code examples
    Return the extracted content as markdown.
    

    Record scrape timestamp for each source (use current date: YYYY-MM-DD format).


    4. Generate Skill

    Skills are modular, self-contained packages. Every skill consists of a required SKILL.md file and optional bundled resources:

    skill-name/
    ├── SKILL.md (required)
    │   ├── YAML frontmatter metadata (required)
    │   │   ├── name: (required)
    │   │   └── description: (required)
    │   └── Markdown instructions (required)
    └── Bundled Resources (optional)
        ├── scripts/          - Executable code (Python/Bash/etc.)
        ├── references/       - Documentation intended to be loaded into context as needed
        └── assets/           - Files used in output (templates, icons, fonts, etc.)
    
    1. Read references/skill_creation_guide.md to understand the format and principles.
    2. Synthesize the learned and extracted information into a new skill.
      • Trigger: Write a description that clearly defines when to use it.
      • Workflow: Create step-by-step instructions.
      • Format: Ensure valid YAML frontmatter and proper file structure.

    5. Save the Skill

    Antigravity supports two types of skills, save a global-workspace if asked.

    • .agent/skills/<skill-folder>/ Workspace-specific
    • ~/.gemini/antigravity/skills/<skill-folder>/ Global (all workspaces)

    Create directory if it doesn't exist, warn user before overwriting existing skill.


    6. Confirm to User

    Report:

    ✓ Created skill: <topic>
      Sources scraped: <N>
      Saved to: .agent/skills/<topic>/SKILL.md
      This skill will auto-trigger when working with <topic>.
    

    Tool Reference

    • search_web: Discover documentation URLs
    • read_url_content: Extract content from static pages
    • browser_subagent: Extract content from JavaScript-heavy sites
    • write_to_file: Save the generated skill

    Critical Rules

    1. Never hallucinate documentation: Only include information from scraped sources.
    2. Never invent APIs: If documentation is unclear, ask the user what to do.
    3. Ask for URLs: If automated discovery fails, ask user for specific URLs.
    4. Verify sources: Prefer official sources over third-party tutorials.

    Требования и возможности

    Источник пакета
    https://github.com/philschmid/self-learning-skill/tree/09474fa110e80cf1aeb27d0ac3b64c8420e7af9f/skills/self-learning

    Файлы версии

    ПутьРазмерSHA256
    SKILL.md4304d2d9d1d3b2cf2920...
    references/skill_creation_guide.md176132a5afb739a212efc...

    Частые вопросы

    Как установить Self Learning?
    Используйте команду npx skills add philschmid/self-learning-skill --skill self-learning или скачайте ZIP-архив.
    Можно ли скачать Self Learning бесплатно?
    Да, опубликованную версию можно скачать из маркетплейса бесплатно.

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    Установить скилл

    Добавьте инструмент одной командой или скачайте проверенный архив версии.

    npx skills add philschmid/self-learning-skill --skill self-learning
    Скачать ZIP
    Версия
    1.0.0+09474fa110e8
    Автор
    Владимир Ломтев
    Репозиторий
    philschmid/self-learning-skill
    GitHub: philschmid/self-learning-skill
    Llm WikiThe foundational knowledge distillation pattern for building and maintaining an AI-powered Obsidian wiki. Based on Andrej Karpathy's LLM Wiki architecture. Use this skill whenever the user wants to understand the wiki pattern, set up a new knowledge base, or needs guidance on the three-layer architecture (raw sources → wiki → schema). Also use when discussing knowledge management strategy, wiki structure decisions, or how to organize distilled knowledge. This is the "theory" skill — other skills handle specific operations (ingesting, querying, linting).