Continuous Learning

Community

mturac

continuous-learning

OpenAI Codexセッションから再利用可能なパターンを自動的に抽出し、将来の使用のために学習済みスキルとして保存します。

Overview

Publisher	mturac
Repository	`everything-openai-codex`
Skill name	`continuous-learning`
Stars	91
Forks	2
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by mturac on GitHub. Read the source before you install it.

Installation

Install the Continuous Learning AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/mturac/everything-openai-codex/tree/main/docs/ja-JP/skills/continuous-learning

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/mturac/everything-openai-codex.git /tmp/everything-openai-codex
mkdir -p .claude/skills
cp -r /tmp/everything-openai-codex/docs/ja-JP/skills/continuous-learning .claude/skills/continuous-learning

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Continuous Learning in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Continuous Learning on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Continuous Learning is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

継続学習スキル

OpenAI Codexセッションを終了時に自動的に評価し、学習済みスキルとして保存できる再利用可能なパターンを抽出します。

動作原理

このスキルは各セッション終了時にStopフックとして実行されます:

セッション評価: セッションに十分なメッセージがあるか確認(デフォルト: 10以上)
パターン検出: セッションから抽出可能なパターンを識別
スキル抽出: 有用なパターンを~/.codex/skills/learned/に保存

設定

config.jsonを編集してカスタマイズ:

json
{
  "min_session_length": 10,
  "extraction_threshold": "medium",
  "auto_approve": false,
  "learned_skills_path": "~/.codex/skills/learned/",
  "patterns_to_detect": [
    "error_resolution",
    "user_corrections",
    "workarounds",
    "debugging_techniques",
    "project_specific"
  ],
  "ignore_patterns": [
    "simple_typos",
    "one_time_fixes",
    "external_api_issues"
  ]
}

パターンの種類

パターン	説明
`error_resolution`	特定のエラーの解決方法
`user_corrections`	ユーザー修正からのパターン
`workarounds`	フレームワーク/ライブラリの癖への解決策
`debugging_techniques`	効果的なデバッグアプローチ
`project_specific`	プロジェクト固有の規約

フック設定

~/.codex/settings.jsonに追加:

json
{
  "hooks": {
    "Stop": [{
      "matcher": "*",
      "hooks": [{
        "type": "command",
        "command": "~/.codex/skills/continuous-learning/evaluate-session.sh"
      }]
    }]
  }
}

Stopフックを使用する理由

軽量: セッション終了時に1回だけ実行
ノンブロッキング: すべてのメッセージにレイテンシを追加しない
完全なコンテキスト: セッション全体のトランスクリプトにアクセス可能

比較ノート (調査: 2025年1月)

vs Homunculus

Homunculus v2はより洗練されたアプローチを採用:

機能	このアプローチ	Homunculus v2
観察	Stopフック(セッション終了時)	PreToolUse/PostToolUseフック(100%信頼性)
分析	メインコンテキスト	バックグラウンドエージェント(Fast)
粒度	完全なスキル	原子的な「本能」
信頼度	なし	0.3-0.9の重み付け
進化	直接スキルへ	本能 → クラスタ → スキル/コマンド/エージェント
共有	なし	本能のエクスポート/インポート

homunculusからの重要な洞察:

"v1はスキルに観察を依存していました。スキルは確率的で、発火率は約50-80%です。v2は観察にフック(100%信頼性)を使用し、学習された振る舞いの原子単位として本能を使用します。"

v2の潜在的な改善

本能ベースの学習 - 信頼度スコアリングを持つ、より小さく原子的な振る舞い
バックグラウンド観察者 - 並行して分析するFastエージェント
信頼度の減衰 - 矛盾した場合に本能の信頼度が低下
ドメインタグ付け - コードスタイル、テスト、git、デバッグなど
進化パス - 関連する本能をスキル/コマンドにクラスタ化

詳細: docs/continuous-learning-v2-spec.mdを参照。

Frequently asked questions

What does the Continuous Learning AI skill do?

OpenAI Codexセッションから再利用可能なパターンを自動的に抽出し、将来の使用のために学習済みスキルとして保存します。

Why use Continuous Learning on TypingMind?

Because you install it once and use it with any model. Continuous Learning is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Continuous Learning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mturac/everything-openai-codex/tree/main/docs/ja-JP/skills/continuous-learning. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Continuous Learning?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Continuous Learning?

As many as you like. As long as a model supports skills, you can use Continuous Learning with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Continuous Learning AI skill free?

Yes. It is published on GitHub by mturac under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Claude Handoff

Hand the current conversation off to a fresh background agent that picks up the work immediately.

Continuous Learning

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

継続学習スキル

動作原理

設定

パターンの種類

フック設定

Stopフックを使用する理由

関連項目

比較ノート (調査: 2025年1月)

vs Homunculus

v2の潜在的な改善

Frequently asked questions

Set up your own AI workspace now

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

継続学習スキル

動作原理

設定

パターンの種類

フック設定

Stopフックを使用する理由

関連項目

比較ノート (調査: 2025年1月)

vs Homunculus

v2の潜在的な改善

Frequently asked questions

Related AI Skills

Set up your own AI workspace now