extract-memorylisted

# extract-memory Analyze a collection of documents and extract a personal writing style profile into a Claude Code memory file. ## What This Skill Does 1. Reads all documents from a given directory or file 2. Analyzes writing patterns, style, tone, vocabulary, themes 3. Generates a structured writing style profile 4. Saves the profile to a memory file (default: `~/.claude/writing-style.md`) ## Supported Input Formats - `.md` — Markdown files - `.txt` — Plain text files - `.pdf` — PDF documents (read via the Read tool) - `.lakebook` — Yuque exports (auto-detected, will run `/convert-lakebook` first) ## Workflow ### Step 1: Identify Input Determine what the user provided: - **Directory path**: Read all supported files in the directory - **Single file path**: Read that one file - **`.lakebook` file**: First convert to Markdown using `python3 ~/Desktop/lakebook-converter/convert.py`, then process the output directory ### Step 2: Sample Documents For large collections (20+ files): - Read all files but sample strategically — pick diverse documents by length and topic - Aim to read at least 15-20 substantial documents (>500 chars each) - Prioritize longer, more expressive documents over short notes For small collections (<20 files): - Read all files completely ### Step 3: Analyze Writing Style Examine the documents and extract the following dimensions: #### Structure Patterns - How do they open articles? (Hook style, question, statement, story) - What's the typical ar