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Documentation Index

Fetch the complete documentation index at: https://docs.ederspark.com/llms.txt

Use this file to discover all available pages before exploring further.

Master Freiya with these tips, tricks, and best practices from experienced users. Whether you’re new to the platform or looking to level up your workflow, you’ll find actionable advice here.

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Organization strategies

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Start with structure

Set up your organizational system before adding many papers: Day one checklist:
1

Define your collections

Create 2-4 core collections based on your projects or topics
2

Establish tag system

Decide on your tagging conventions (see recommendations below)
3

Create templates

Write a note template for consistent paper summaries
4

Set up color code

Decide what each highlight color means for you
The 10 minutes you spend setting up organization will save hours later.

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The “Three-Tag Rule”

Every paper should have at least three tags:
  1. Status tag - Reading progress (to-read, reading, read)
  2. Importance tag - Priority level (key-paper, supporting, reference)
  3. Topic tag - Subject area (methodology, theory, application)
Example: A paper might be tagged: reading, key-paper, neural-networks This system ensures papers are both findable and prioritized.

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Collection naming patterns

Use consistent, descriptive names that scale: ✅ Good patterns: 
Project-based:
- "Thesis - Ch1 - Introduction"
- "Thesis - Ch2 - Literature Review"
- "Grant Proposal - NSF 2025"

Topic-based:
- "ML - Deep Learning"
- "ML - Computer Vision"
- "ML - NLP"

Course-based:
- "CS601 - Machine Learning"
- "Seminar - Fall 2024"
❌ Avoid: 
- "Papers"
- "Stuff"
- "Collection 1"
- "Temp"
- "Misc"

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Reading efficiently

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The three-pass method

Don’t try to read every paper deeply. Use this approach:
Goal: Decide if worth reading
  • Read title and abstract
  • Look at figures and captions
  • Check references (any familiar?)
  • Skim conclusions
Decision: Keep, maybe, or discard
Only about 20% of papers deserve a third pass. Be selective with your time.

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Active reading techniques

While reading, actively engage:
  • Question everything - Don’t accept claims blindly
  • Make predictions - Guess results before reading them
  • Connect ideas - Link to other papers you’ve read
  • Visualize - Draw diagrams of concepts
  • Summarize sections - Pause and recap in your own words
In Freiya:
  • Add comments with your questions
  • Use purple highlights for “to investigate”
  • Link related papers in notes
  • Draw on PDFs (coming soon)
  • Write section summaries in comments

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Speed reading papers

Techniques for faster reading:
  1. Read abstract first - Sets context for everything else
  2. Study visuals - Figures often tell the whole story
  3. Skip intro on first read - Usually literature review you know
  4. Read results before methods - Understand what before how
  5. Save background for later - Deep dive only when needed
Don’t feel guilty about skimming. Your goal is understanding, not word-by-word reading.

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Annotation strategies

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Develop a personal system

Example highlighting system:
What I HighlightColorWhy
Core argumentYellowThe paper’s main claim
EvidenceGreenData supporting the claim
Quotable passagesBlueFor citing in my writing
Problems/limitationsRedWeaknesses to discuss
My ideasPurpleThoughts sparked by reading
ExamplesOrangeUseful illustrations
Stick to your system! Consistency makes review much easier.

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Comment like you’re teaching

Write comments as if explaining to someone else: Instead of: “Important” Write: “This shows that X causes Y, which contradicts Smith’s finding. Possible confound: Z wasn’t controlled.” Instead of: “Good method” Write: “Their use of repeated measures eliminates between-subject variance. Could adapt this for my study.” Future you will appreciate the context.

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Use categorization

Beyond colors, categorize highlights:
  • Methodology - How they did it
  • Results - What they found
  • Discussion - What it means
  • Limitations - What’s problematic
  • Future work - What’s next
Filter by category when reviewing for specific purposes.

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AI chat best practices

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Prompt engineering tips

Be specific: ❌ “Tell me about this paper” ✅ “Summarize the three main findings from the Results section and explain their statistical significance” ❌ “How does this work?” ✅ “Explain how their attention mechanism differs from standard self-attention, and why they claim it’s more efficient” Provide context: Instead of: “What are the limitations?” Try: “I’m writing a literature review on medical imaging. What are the main limitations of this approach that I should mention, particularly regarding generalization to different populations?”

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Iterative questioning

Build on previous responses: 
You: What methodology did the authors use?

AI: [Explains methodology]

You: What are the advantages of this approach over traditional methods?

AI: [Explains advantages]

You: Given those advantages, why might they have still seen the limitations mentioned in the Discussion?

AI: [Deeper analysis]
This conversational approach often yields better insights than single questions.

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Verify AI responses

Always verify AI-provided information:
  • Cross-check facts against the actual paper
  • Verify citations in the original source
  • Consult experts for critical decisions
  • Use multiple sources for important claims
  • Never cite the AI - cite the original paper
AI is a research assistant, not a replacement for critical thinking.

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Search and discovery

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Advanced search techniques

Use specific terms:
  • DOI searches for exact papers
  • Author name + topic
  • Methodology-specific terms
  • Year ranges for recent work
Google Scholar tips:
  • Use quotes for exact phrases: "attention mechanism"
  • Exclude terms with minus: -review (exclude reviews)
  • Site-specific: site:arxiv.org
  • Date ranges: Tools → Custom range
In Freiya:
  • Search within collections
  • Filter by tags first, then search
  • Use autocomplete suggestions
  • Try alternative terms if no results

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Building your library

Quality over quantity:
  • Don’t add papers you’ll never read
  • Be selective in your criteria
  • Delete papers that turn out irrelevant
  • Aim for a curated, useful library
Growth strategies:
Weekly additions: 2-5 papers
  • Deep engagement with each
  • Thorough notes and highlights
  • Complete reading before adding more
Best for: Deep expertise in narrow area

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Productivity hacks

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Keyboard shortcuts mastery

Learn these essentials:
TaskShortcutTime Saved
New chatCtrl/Cmd + N3 seconds
Add paperCtrl/Cmd + P2 seconds
Search libraryCtrl/Cmd + F2 seconds
Quick commandCtrl/Cmd + K3 seconds
Do the math: Using shortcuts 20 times/day × 2.5 seconds = 50 seconds/day = 300 hours/year saved! See all shortcuts →

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Batch similar tasks

Instead of: Add paper → tag → add notes → repeat Try: Add 5 papers → tag all 5 → write notes for all 5 Batch operations save mental switching costs:
  • Add papers in one session
  • Tag papers in another
  • Review and annotate in a third
  • Weekly note-writing session

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Time blocking

Sample research schedule:
TimeActivity
Mon 9-10amPaper discovery and addition
Mon 2-3pmDeep reading (Pass 3)
Wed 9-11amAnnotation and note-taking
Fri 3-4pmWeekly organization and planning
Consistent routines build momentum and reduce decision fatigue.

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Collaboration tips

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Sharing effectively

When sharing chats:
  • Remove sensitive or unpublished information
  • Add context at the top
  • Check that it makes sense standalone
  • Include relevant paper links
When sharing paper lists:
  • Export with notes/tags
  • Add a README explaining organization
  • Include citation file (BibTeX)
  • Note any access restrictions

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Team coordination

For research groups:
  1. Standardize tagging - Agree on tag conventions
  2. Shared naming - Consistent collection/paper naming
  3. Regular sync - Weekly coordination meetings
  4. Export often - Share progress via exports
  5. Document workflow - Write down your team’s process

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Subscription optimization

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Maximizing free tier

With 5 papers:
  • Focus on truly essential papers
  • Use one “evergreen” slot for long-term reference
  • Rotate other 4 slots as needed
  • Export notes before deleting papers
  • Leverage unlimited AI chat to compensate
With 2 collections:
  • One for current project
  • One for general reference
  • Use tags extensively instead of more collections

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When to upgrade

Signs you need Pro:
  • Hit 5-paper limit within first week
  • Need more than 2 collections
  • Want advanced AI models
  • Doing serious literature review (20+ papers)
Signs you need Nova:
  • Need specialized AI models for your field
  • Require domain-specific analysis
  • Want highest quality AI responses
  • Large complex research projects (100+ papers)

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Common mistakes to avoid

Problem: Library becomes overwhelming, nothing gets readSolution: Be selective. Ask “Will I actually read this?” before adding
Problem: Papers accumulate without organizationSolution: Tag while adding. It takes 5 seconds now vs. 5 minutes later
Problem: Highlights become meaninglessSolution: Highlight selectively. If everything is important, nothing is
Problem: Can’t remember papers laterSolution: Write 2-3 sentence summary immediately after reading
Problem: Highlights and notes go unusedSolution: Export and review highlights when writing
Problem: Can’t interpret your own highlights laterSolution: Define your system once and stick to it
Problem: Spending too long organizing vs. actually workingSolution: Done is better than perfect. 80/20 rule applies

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Platform-specific tips

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For graduate students

  • Create collections per thesis chapter
  • Tag papers by “cite in intro”, “cite in methods”, etc.
  • Use AI to help understand difficult concepts
  • Export highlights when drafting
  • Track advisor recommendations with special tag

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For professors

  • Collections per course you teach
  • Share reading lists with students (export)
  • Track student paper recommendations
  • Organize by research area for grant writing
  • Use for tenure/promotion documentation

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For research teams

  • Standardized tagging system
  • Regular paper-sharing sessions
  • Collaborative annotations (coming soon)
  • Shared chat collections
  • Export-based workflow

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For interdisciplinary researchers

  • Separate collections per field
  • Field-specific tag prefixes (bio:, cs:, psych:)
  • Use AI to bridge terminology gaps
  • “Bridge papers” collection for cross-field work
  • Institution search for finding collaborators

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Power user tricks

Custom CSS

Use browser extensions to customize Freiya’s appearance

Automation

Use browser automation for repetitive tasks

External sync

Auto-export to cloud storage with scripts

API integration

Connect Freiya to other tools (coming soon)

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Troubleshooting tips

If something isn’t working:
  1. Refresh the page - Fixes 50% of issues
  2. Clear cache - Fixes another 25%
  3. Try incognito mode - Rules out extensions
  4. Check internet - Connection issues common
  5. Different browser - Browser-specific bugs exist
  6. Contact support - They’re responsive and helpful

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Continuous improvement

Monthly reflection questions:
  • What’s working well in my workflow?
  • What feels clunky or inefficient?
  • Am I actually using my highlights and notes?
  • Is my organizational system still serving me?
  • What could I automate or simplify?
Iterate and refine - Your workflow should evolve with your needs.

Research workflow

Comprehensive workflow guide

Keyboard shortcuts

Master all shortcuts

AI chat guide

Advanced AI usage tips

PDF viewer

Annotation best practices
Remember: The best workflow is the one you’ll actually use. Start simple, then optimize as you go.