Brain Ingest

Step 1: Identify Input Type

Determine what the user provided:

If no input was provided, prompt: "What would you like to ingest? Provide a file path, URL, or paste the text."

Step 2: Extract Raw Content

For PDF files

• Read the PDF content
• Extract text, preserving structure (headings, lists, paragraphs)
• Note any images or diagrams that cannot be extracted (mention them in the output)

For URLs

• Fetch the page content
• Extract the main article/content body (strip navigation, ads, footers)
• Capture the title, author, publication date if available
• Save the source URL for attribution

For raw text

• Use the text as-is
• Attempt to identify structure (headings, lists, paragraphs)

Step 3: Understand Salience

Ask the user what matters about this content before processing:

I have the content loaded. Before I extract key points, help me understand what is salient for you:

1. What is your goal with this content? (learning, reference, decision-making, project context)
2. Any specific sections or topics you care about most?
3. How detailed should the extraction be? (high-level summary / key points / detailed notes)
4. Any existing vault notes this relates to?

Or just say "general" and I will extract the most important points.

Use the user's guidance to focus the extraction. If the user says "general," extract broadly.

Step 4: Process Content

Based on the salience guidance, extract and structure the content:

Key Points Extraction

• Identify the main thesis or purpose
• Extract key arguments, findings, or concepts
• Note important data points, quotes, or examples
• Identify action items or implications for the user

Structure the Output

---
date: YYYY-MM-DD
tags: [{topic-tags}]
type: reference
source: "{URL or filename or 'raw input'}"
author: "{if known}"
ingested: YYYY-MM-DD
status: staging
---

# {Title}

> **Source:** {URL/file/raw}
> **Ingested:** {date} via ingest skill

## Summary
{2-5 sentence summary of the content}

## Key Points
- {main takeaway 1}
- {main takeaway 2}
- {main takeaway 3}

## Detailed Notes
{structured notes based on salience guidance}

## Relevance
{how this connects to existing vault content}
- Related: [[existing note 1]]
- Related: [[existing note 2]]

## Questions / Follow-ups
- {anything raised by the content worth exploring}

## Raw Quotes
> "{important quote 1}" -- {attribution}
> "{important quote 2}" -- {attribution}

Step 5: Add Wikilinks

Cross-reference the ingested content with the existing vault:

1. Read Machine/Memory/entities.md for known entities.
2. Scan Human/Projects/ for active projects.
3. Add [[wikilinks]] wherever the content references known entities, projects, or concepts that have existing notes.
4. Suggest new wikilinks for concepts that do not yet have notes but probably should.

Step 6: Save to Staging

Save the processed note to Machine/ (the AI zone), NOT directly to Human/:

Path: Machine/ingested/{YYYY-MM-DD}-{slug}.md

Where {slug} is a kebab-case version of the title (e.g., 2025-01-15-api-design-patterns.md).

Create the Machine/ingested/ directory if it does not exist.

Step 7: Present and Offer Integration

Show the user what was created:

Ingested and processed. Here is what I saved:

File: Machine/ingested/{filename}.md
Source: {source}
Key points: {count}
Wikilinks: {count} connections to existing notes

Preview:
{show the Summary and Key Points sections}

Actions:
1. Move to Human/ (integrate into your notes)
2. Edit first (open for review)
3. Leave in Machine/ingested/ for now
4. Discard

What would you like to do?

If the user chooses to integrate:

• Move the file to the appropriate Human/ subdirectory
• Update the status frontmatter field from staging to integrated
• Update today's daily note with a log entry

Advanced: PDF and Document Pipeline

For importing large or messy documents (PDFs, DOCX, Excel, annual reports), use this pipeline to extract signal from noise:

Sub-step A: Organize by File Type

If given a folder of mixed files:

1. Scan the directory for file types
2. Create subfolders: PDFs/, DOCX/, Spreadsheets/, Other/
3. Move files to appropriate subfolders
4. Report the organization to the user before proceeding

Sub-step B: Extract and Synthesize

For each document:

1. Extract raw text using available tools (Read for text files, Bash for pdftotext if available)

2. Synthesize with a focused prompt:

   You are distilling [document type] into a knowledge artifact.
   Extract ONLY:
   - Core concepts and definitions
   - Key decisions or findings
   - Actionable insights
   - Important data points or metrics
   - Named entities (people, companies, products)
   
   Ignore: formatting noise, headers/footers, boilerplate, redundant text.
   Format as clean markdown with clear sections.
   

3. Create a cheat-sheet note — not a full copy, just the signal:

   ---
   date: YYYY-MM-DD
   tags: [ingested, {document-type}]
   type: reference
   source: {original filename}
   ---
   
   # {Document Title} — Key Points
   
   {synthesized content}
   

Sub-step C: Import to Vault

Save synthesized notes to Human/Projects/{topic}/ or ask user for preferred location.

With Obsidian CLI:

obsidian open "{note-path}"  # open the new note to verify

Sub-step D: Link to Related Notes

After importing, suggest connections:

• Search for existing notes on the same topic
• Offer to add [[wikilinks]] to related content
• Offer to update Machine/Memory/entities.md with new entities discovered