Instapaper Import

Parse Instapaper highlight exports and create slipbox entries for user's notes.

Input Format

# [[Article Title](url)]
> Original highlight from article (SKIP)
User's note about the highlight (IMPORT)
> Another highlight (SKIP)
Another user note (IMPORT)

Key distinction:

• > lines = Original article highlights → Skip these
• Plain text lines = User's own ideas/takeaways → Import these as notes

Parsing Rules

Header Line

1. Extract title from: # [[Title](url)]
2. URL may be instapaper-private://... (private) or regular URL
3. Source type: article
4. Author: null (Instapaper doesn't include author)

Content Lines

1. Lines starting with > = original highlights → skip
2. Plain text lines after > lines = user notes → import
3. Empty lines → skip
4. Each user note becomes a separate slipbox entry

Workflow

1. Parse header → extract article title and URL
2. Extract user notes → collect plain text lines (not starting with >)
3. Precheck → show user: article title, note count, ask for confirmation
4. On confirmation → for each note, invoke slipbot:
   • Type: note (- prefix)
   • Source: ~ article, {title}
   • Let slipbot handle: filename, tags, links, graph update
5. Report → count of notes created

Example

Input:

# [[How to Learn Faster](https://example.com/article)]
> Get feedback more often
To learn faster we need faster feedback loops.
> Latent learning occurs without reinforcement
Testing yourself proactively speeds up learning.

Extracted notes:

1. "To learn faster we need faster feedback loops."
2. "Testing yourself proactively speeds up learning."

Slipbot calls:

- To learn faster we need faster feedback loops. ~ article, How to Learn Faster
- Testing yourself proactively speeds up learning. ~ article, How to Learn Faster

Edge Cases

• No user notes (only > lines): Report "no notes to import"
• Multi-line user notes: Treat each paragraph as separate note
• Title with special chars: Preserve as-is for source metadata