continuous-learning
About
The continuous-learning skill automatically analyzes Claude Code sessions to identify reusable patterns and save them as learned skills for future use. It runs as a stop hook after each session, extracting useful techniques like error resolutions and debugging methods. Developers should enable this skill to build a personalized knowledge base from their coding interactions over time.
Quick Install
Claude Code
Recommended/plugin add https://github.com/majiayu000/claude-skill-registrygit clone https://github.com/majiayu000/claude-skill-registry.git ~/.claude/skills/continuous-learningCopy and paste this command in Claude Code to install this skill
Documentation
持續學習技能
自動評估 Claude Code 工作階段結束時的內容,提取可重用模式並儲存為學習技能。
運作方式
此技能作為 Stop hook 在每個工作階段結束時執行:
- 工作階段評估:檢查工作階段是否有足夠訊息(預設:10+ 則)
- 模式偵測:從工作階段識別可提取的模式
- 技能提取:將有用模式儲存到
~/.claude/skills/learned/
設定
編輯 config.json 以自訂:
{
"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"
]
}
模式類型
| 模式 | 描述 |
|---|---|
error_resolution | 特定錯誤如何被解決 |
user_corrections | 來自使用者修正的模式 |
workarounds | 框架/函式庫怪異問題的解決方案 |
debugging_techniques | 有效的除錯方法 |
project_specific | 專案特定慣例 |
Hook 設定
新增到你的 ~/.claude/settings.json:
{
"hooks": {
"Stop": [{
"matcher": "*",
"hooks": [{
"type": "command",
"command": "~/.claude/skills/continuous-learning/evaluate-session.sh"
}]
}]
}
}
為什麼用 Stop Hook?
- 輕量:工作階段結束時只執行一次
- 非阻塞:不會為每則訊息增加延遲
- 完整上下文:可存取完整工作階段記錄
相關
- Longform Guide - 持續學習章節
/learn指令 - 工作階段中手動提取模式
比較筆記(研究:2025 年 1 月)
vs Homunculus (github.com/humanplane/homunculus)
Homunculus v2 採用更複雜的方法:
| 功能 | 我們的方法 | Homunculus v2 |
|---|---|---|
| 觀察 | Stop hook(工作階段結束) | PreToolUse/PostToolUse hooks(100% 可靠) |
| 分析 | 主要上下文 | 背景 agent(Haiku) |
| 粒度 | 完整技能 | 原子「本能」 |
| 信心 | 無 | 0.3-0.9 加權 |
| 演化 | 直接到技能 | 本能 → 聚類 → 技能/指令/agent |
| 分享 | 無 | 匯出/匯入本能 |
來自 homunculus 的關鍵見解:
"v1 依賴技能進行觀察。技能是機率性的——它們觸發約 50-80% 的時間。v2 使用 hooks 進行觀察(100% 可靠),並以本能作為學習行為的原子單位。"
潛在 v2 增強
- 基於本能的學習 - 較小的原子行為,帶信心評分
- 背景觀察者 - Haiku agent 並行分析
- 信心衰減 - 如果被矛盾則本能失去信心
- 領域標記 - code-style、testing、git、debugging 等
- 演化路徑 - 將相關本能聚類為技能/指令
參見:/Users/affoon/Documents/tasks/12-continuous-learning-v2.md 完整規格。
GitHub Repository
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