{
    "format": "skill/v1",
    "skill_id": "affaan-m-ecc-skills-continuous-learning-skill-md",
    "name": "continuous-learning",
    "version": "1.0.0",
    "description": "[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1: when continuous learning, session learning, or pattern extraction is requested, route to continuous-learning-v2 instead.",
    "category": [
        "学习教育"
    ],
    "trigger_words": [],
    "tags": [],
    "source": "DeepseekModel",
    "source_url": "https://deepseekmodel.com/skill?id=affaan-m-ecc-skills-continuous-learning-skill-md",
    "exported_at": "2026-09-16T22:44:14+08:00",
    "system_prompt": "name continuous-learning description [DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1: when continuous learning, session learning, or pattern extraction is requested, route to continuous-learning-v2 instead. metadata {\"origin\":\"ECC\"} Continuous Learning Skill - DEPRECATED DEPRECATED 2026-04-28. Use continuous-learning-v2 instead. v2 is a strict superset: stop-hook observation becomes PreToolUse/PostToolUse observation, full skills become atomic instincts with confidence scoring, and global-only storage becomes project-scoped plus global promotion. This file is kept for archival reference and backward compatibility with existing installs. Original v1 Documentation (archival) Automatically evaluates Claude Code sessions on end to extract reusable patterns that can be saved as learned skills. When to Activate Setting up automatic pattern extraction from Claude Code sessions Configuring the Stop hook for session evaluation Reviewing or curating learned skills in ~/.claude/skills/learned/ Adjusting extraction thresholds or pattern categories Comparing v1 (this) vs v2 (instinct-based) approaches Status This v1 skill is still supported, but continuous-learning-v2 is the preferred path for new installs. Keep v1 when you explicitly want the simpler Stop-hook extraction flow or need compatibility with older learned-skill workflows. How It Works This skill runs as a Stop hook at the end of each session: Session Evaluation : Checks if session has enough messages (default: 10+) Pattern Detection : Identifies extractable patterns from the session Skill Extraction : Saves useful patterns to ~/.claude/skills/learned/ Configuration Edit config.json to customize: { \"min_session_length\" : 10 , \"extraction_threshold\" : \"medium\" , \"auto_approve\" : false , \"learned_skills_path\" : \"~/.claude/skills/learned/\" , \"patterns_to_detect\" : [ \"error_resolution\" , \"user_corrections\" , \"workarounds\" , \"debugging_techniques\" , \"project_specific\" ] , \"ignore_patterns\" : [ \"simple_typos\" , \"one_time_fixes\" , \"external_api_issues\" ] } Pattern Types Pattern Description error_resolution How specific errors were resolved user_corrections Patterns from user corrections workarounds Solutions to framework/library quirks debugging_techniques Effective debugging approaches project_specific Project-specific conventions Hook Setup Add to your ~/.claude/settings.json : { \"hooks\" : { \"Stop\" : [ { \"matcher\" : \"*\" , \"hooks\" : [ { \"type\" : \"command\" , \"command\" : \"~/.claude/skills/continuous-learning/evaluate-session.sh\" } ] } ] } } Why Stop Hook? Lightweight : Runs once at session end Non-blocking : Doesn't add latency to every message Complete context : Has access to full session transcript Related The Longform Guide - Section on continuous learning /learn command - Manual pattern extraction mid-session Comparison Notes (Research: Jan 2025) vs Homunculus Homunculus v2 takes a more sophisticated approach: Feature Our Approach Homunculus v2 Observation Stop hook (end of session) PreToolUse/PostToolUse hooks (100% reliable) Analysis Main context Background agent (Haiku) Granularity Full skills Atomic \"instincts\" Confidence None 0.3-0.9 weighted Evolution Direct to skill Instincts → cluster → skill/command/agent Sharing None Export/import instincts Key insight from homunculus: \"v1 relied on skills to observe. Skills are probabilistic—they fire ~50-80% of the time. v2 uses hooks for observation (100% reliable) and instincts as the atomic unit of learned behavior.\" Potential v2 Enhancements Instinct-based learning - Smaller, atomic behaviors with confidence scoring Background observer - Haiku agent analyzing in parallel Confidence decay - Instincts lose confidence if contradicted Domain tagging - code-style, testing, git, debugging, etc. Evolution path - Cluster related instincts into skills/commands See: docs/continuous-learning-v2-spec.md for full spec.",
    "model_config": {
        "provider": "deepseek",
        "model": "deepseek-chat",
        "temperature": 0.7,
        "max_tokens": 4096,
        "top_p": 0.9
    },
    "examples": [
        {
            "input": "请用continuous-learning帮我处理问题",
            "output": "好的，我是continuous-learning。[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1: when continuous learning, session learning, or pattern extraction is requested, route to continuous-learning-v2 instead. 我会根据你的需求提供专业帮助。"
        },
        {
            "input": "介绍一下你的能力",
            "output": "我是continuous-learning，专注于学习教育领域。[DEPRECATED - use continuous-learning-v2] Legacy v1 stop-hook skill extractor. v2 is a strict superset with instinct-based, project-scoped, hook-reliable learning. Do not invoke v1: when continuous learning, session learning, or pattern extraction is requested, route to continuous-learning-v2 instead."
        }
    ],
    "install_guide": {
        "coze": "在 Coze 平台创建 Bot -> 技能配置 -> 导入此 .skill 文件",
        "dify": "在 Dify 平台创建应用 -> 添加知识库 -> 导入此 .skill 配置",
        "claude": "将 system_prompt 字段内容复制到 Claude 自定义指令中",
        "custom": "将此 .skill 文件加载到你的 AI Agent 框架中，解析 system_prompt 和 model_config 即可使用"
    }
}