deep-dive-notes
Transcribe handwritten multi-source research notes from reMarkable PDFs or paper photos. Trigger phrase "process deep dive notes". Handles research compilations with multiple sources per document. Converts handwriting to markdown, applies formatting conventions, generates metadata, creates AI summaries, and appends quotes to a central quotes file. Notes may be in Czech or English.
安装与使用
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
查看来源 ↗使用指南技能说明
Deep Dive Notes Processor
Transcribe handwritten multi-source research notes into structured Obsidian notes.
Trigger
User says "process deep dive notes" and provides either:
- A PDF file (reMarkable export)
- Multiple image files (photos of paper notes)
Language
Notes may be in Czech or English. Preserve the original language throughout. Do not translate.
Workflow
1. Convert and Transcribe
For PDF input:
from pdf2image import convert_from_path
images = convert_from_path('notes.pdf', dpi=150)
for i, img in enumerate(images):
img.save(f'page_{i+1}.png', 'PNG')
For image input: Accept images directly and process in order.
Then visually read and transcribe each page.
2. Verify Content Type
Deep dive notes contain multiple sources (multiple H1 headings), each representing a different article, video, or resource.
If user provides single-source notes, suggest: "This looks like single-source book notes. Should I use 'process book notes' instead?"
3. Apply Formatting Rules
See ../shared/formatting-rules.md for complete conventions. Key rules:
-
!at bullet start → italics -
!!!at bullet start → bold - Underscored words → bold
- Numbered sequences → numbered lists
- H1 (
#) marks source titles - Quotes:
Author: *"Quote text"*
4. Collect Metadata
Ask user for:
- Resources list (URLs to original sources)
Then query Obsidian for existing tags:
obsidian-mcp-tools:search_vault_simple with relevant keywords
Select 3-5 tags that match the vault's existing taxonomy.
5. Generate Summary
If transcribed content exceeds ~1 A4 of text, generate a 1-3 paragraph summary covering:
- Core tension or theme
- Key frameworks or approaches
- Critical questions or insights
Place summary after frontmatter, before raw transcription.
6. Build Frontmatter
---
title: [Derived from content or user input]
date_created: [YYYY-MM-DD]
source_type: research
tags:
- [3-5 relevant tags from vault]
resources:
- [URL 1]
- [URL 2]
---
7. Handle Quotes
If transcription contains quotes (format: Author: "Quote text"):
In transcription:
- Author: *"Quote text"*
Append to Obsidian quotes file 10 - 🧠 Knowledge/3 - 📚 Resources/Learning/Quotes.md:
- Author: "Quote text"
8. Save to Obsidian
Create file in inbox: 02 - 📩 Inbox/[Title].md
Use obsidian-mcp-tools:create_vault_file with the complete markdown content.
9. Add Related Notes
Query Obsidian for related existing notes and add a ## Related notes section with wiki-links at the end.
Output Structure
---
[frontmatter]
---
## Summary
[AI-generated summary if content is long enough]
---
# From "[Source 1]"
- [transcribed bullets with formatting]
- *important point*
- **very important point**
- Author: *"Quote text"*
# From "[Source 2]"
...
## Related notes
- [[Related Note 1]]
- [[Related Note 2]]
使用示例
查看来源仓库中的使用示例与配置说明。
查看来源 ↗来源历史
- 收录时间
- 2026-01-20
- 索引更新时间
- 2026-01-26
- Branch
- main
收录与同步日期属于本站记录。源码修改历史请查看来源仓库。
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