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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.