Remembering by Design, Not by Memory: The 'Recall Trigger' Note-Taking Method Using LLMs and Logseq

3 Steps to Turn Interesting Repositories into Letters to Your Future Self

Repository link at the end of the article 🔗

You find an interesting repository on GitHub. You think, 'This could be useful.' But three days later, you've forgotten it.

That has been happening to me for a long time.

The solution wasn't to train my memory. It was to design the timing for remembering.

Overview of the Workflow

1. 気になるリポジトリに出会う
        ↓
2. LLMに「これは何の系譜ですか？」と問う
        ↓
3. Logseq形式（階層・タグ・トリガー）で出力させる
        ↓
4. 日誌ページ ＋ 再評価トリガーページに保存
        ↓
5. トリガーが来たとき、自然に思い出せる

Step 1: Ask the LLM, 'What is the lineage of this?'

Pass the repository URL as is and ask this:

Instead of reading the feature list, first understand what problem this tool was created to solve.

For example, when I passed the 'headroom' repository, this was the answer I got back.

• SmartCrusher is an extension of data serialization optimization

• CodeCompressor is an extension of compiler technology (AST analysis)

• headroom learn automatically generates CLAUDE.md from failure logs

A lineage that I wouldn't have noticed just by looking at the feature names becomes visible with a single question.

Step 2: Have it output in Logseq format

This is all the instruction you need for the LLM.

Output example:

- headroom [[コンテキスト圧縮]] [[AIエージェント]]
  - LLMに渡す前にコンテキストを圧縮する中間層
  - ローカル動作・可逆・MCP対応
  - 3エンジン構成
    - SmartCrusher（JSON）
    - CodeCompressor（AST）
    - Kompress-base（テキスト）
  - `headroom learn` — 失敗ログを CLAUDE.md に自動書き込み
  - 再評価トリガー: [[Claude Code]] を本格利用し始めたとき
  - ref: https://github.com/chopratejas/headroom

What is important here is the "re-evaluation trigger" line.

Write down "when you should open this note" along with it. Without this, it will end up buried in your daily journals.

Step 3: Place it in two locations

• Journal page: A record of when you encountered it

• Trigger page: A topic page that serves as a condition, such as [[Claude Code]]

This is where Logseq's bidirectional linking shines. When you open the [[Claude Code]] page, the headroom note automatically surfaces. You can recall it by context, not by chronology.

Things I noticed

While running this workflow, I suddenly realized something.

Converting to Logseq format is, in itself, a form of structured compression.

The moment you decide "what to make a page link (tag)," you are selecting and discarding meanings. Just as headroom compresses context before passing it to an LLM, humans also compress information before saving it to Logseq.

By researching the tools, the way I use them has changed.

#Logseq #PKM #NoteTakingMethod #AItoolUsage #Craftsmanship