Research Information Lookup

Overview

This skill enables real-time research information lookup using Perplexity's Sonar models through OpenRouter. It intelligently selects between Sonar Pro Search (fast, efficient lookup) and Sonar Reasoning Pro (deep analytical reasoning) based on query complexity. The skill provides access to current academic literature, recent studies, technical documentation, and general research information with proper citations and source attribution.

When to Use This Skill

Use this skill when you need:

• Current Research Information: Latest studies, papers, and findings in a specific field
• Literature Verification: Check facts, statistics, or claims against current research
• Background Research: Gather context and supporting evidence for scientific writing
• Citation Sources: Find relevant papers and studies to cite in manuscripts
• Technical Documentation: Look up specifications, protocols, or methodologies
• Recent Developments: Stay current with emerging trends and breakthroughs
• Statistical Data: Find recent statistics, survey results, or research findings
• Expert Opinions: Access insights from recent interviews, reviews, or commentary

Visual Enhancement with Scientific Schematics

When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.

If your document does not already contain schematics or diagrams:

• Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
• Simply describe your desired diagram in natural language
• Nano Banana Pro will automatically generate, review, and refine the schematic

For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text. How to generate schematics:

python scripts/generate_schematic.py "your diagram description" -o figures/output.png

The AI will automatically:

• Create publication-quality images with proper formatting
• Review and refine through multiple iterations
• Ensure accessibility (colorblind-friendly, high contrast)
• Save outputs in the figures/ directory

When to add schematics:

• Research information flow diagrams
• Query processing workflow illustrations
• Model selection decision trees
• System integration architecture diagrams
• Information retrieval pipeline visualizations
• Knowledge synthesis frameworks
• Any complex concept that benefits from visualization

For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.

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Core Capabilities

1. Academic Research Queries

Search Academic Literature: Query for recent papers, studies, and reviews in specific domains:

Query Examples:
- "Recent advances in CRISPR gene editing 2024"
- "Latest clinical trials for Alzheimer's disease treatment"
- "Machine learning applications in drug discovery systematic review"
- "Climate change impacts on biodiversity meta-analysis"

Expected Response Format:

• Summary of key findings from recent literature
• Citation of 3-5 most relevant papers with authors, titles, journals, and years
• Key statistics or findings highlighted
• Identification of research gaps or controversies
• Links to full papers when available

2. Technical and Methodological Information

Protocol and Method Lookups: Find detailed procedures, specifications, and methodologies:

Query Examples:
- "Western blot protocol for protein detection"
- "RNA sequencing library preparation methods"
- "Statistical power analysis for clinical trials"
- "Machine learning model evaluation metrics"

Expected Response Format:

• Step-by-step procedures or protocols
• Required materials and equipment
• Critical parameters and considerations
• Troubleshooting common issues
• References to standard protocols or seminal papers

3. Statistical and Data Information

Research Statistics: Look up current statistics, survey results, and research data:

Query Examples:
- "Prevalence of diabetes in US population 2024"
- "Global renewable energy adoption statistics"
- "COVID-19 vaccination rates by country"
- "AI adoption in healthcare industry survey"

Expected Response Format:

• Current statistics with dates and sources
• Methodology of data collection
• Confidence intervals or margins of error when available
• Comparison with previous years or benchmarks
• Citations to original surveys or studies

4. Citation and Reference Assistance

Citation Finding: Locate relevant papers and studies for citation in manuscripts:

Query Examples:
- "Foundational papers on transformer architecture"
- "Seminal works in quantum computing"
- "Key studies on climate change mitigation"
- "Landmark trials in cancer immunotherapy"

Expected Response Format:

• 5-10 most influential or relevant papers
• Complete citation information (authors, title, journal, year, DOI)
• Brief description of each paper's contribution
• Citation impact metrics when available (h-index, citation count)
• Journal impact factors and rankings

Automatic Model Selection

This skill features intelligent model selection based on query complexity:

Model Types

1. Sonar Pro Search (perplexity/sonar-pro-search)

• Use Case: Straightforward information lookup
• Best For:

- Simple fact-finding queries

- Recent publication searches

- Basic protocol lookups

- Statistical data retrieval

• Speed: Fast responses
• Cost: Lower cost per query

2. Sonar Reasoning Pro (perplexity/sonar-reasoning-pro)

• Use Case: Complex analytical queries requiring deep reasoning
• Best For:

- Comparative analysis ("compare X vs Y")

- Synthesis of multiple studies

- Evaluating trade-offs or controversies

- Explaining mechanisms or relationships

- Critical analysis and interpretation

• Speed: Slower but more thorough
• Cost: Higher cost per query, but provides deeper insights

Complexity Assessment

The skill automatically detects query complexity using these indicators:

Reasoning Keywords (triggers Sonar Reasoning Pro):

• Analytical: compare, contrast, analyze, analysis, evaluate, critique
• Comparative: versus, vs, vs., compared to, differences between, similarities
• Synthesis: meta-analysis, systematic review, synthesis, integrate
• Causal: mechanism, why, how does, how do, explain, relationship, causal relationship, underlying mechanism
• Theoretical: theoretical framework, implications, interpret, reasoning
• Debate: controversy, conflicting, paradox, debate, reconcile
• Trade-offs: pros and cons, advantages and disadvantages, trade-off, tradeoff, trade offs
• Complexity: multifaceted, complex interaction, critical analysis

Complexity Scoring:

• Reasoning keywords: 3 points each (heavily weighted)
• Multiple questions: 2 points per question mark
• Complex sentence structures: 1.5 points per clause indicator (and, or, but, however, whereas, although)
• Very long queries: 1 point if >150 characters
• Threshold: Queries scoring ≥3 points trigger Sonar Reasoning Pro

Practical Result: Even a single strong reasoning keyword (compare, explain, analyze, etc.) will trigger the more powerful Sonar Reasoning Pro model, ensuring you get deep analysis when needed. Example Query Classification:

✅ Sonar Pro Search (straightforward lookup):

• "Recent advances in CRISPR gene editing 2024"
• "Prevalence of diabetes in US population"
• "Western blot protocol for protein detection"

✅ Sonar Reasoning Pro (complex analysis):

• "Compare and contrast mRNA vaccines vs traditional vaccines for cancer treatment"
• "Explain the mechanism underlying the relationship between gut microbiome and depression"
• "Analyze the controversy surrounding AI in medical diagnosis and evaluate trade-offs"

Manual Override

You can force a specific model using the force_model parameter:

# Force Sonar Pro Search for fast lookup
research = ResearchLookup(force_model='pro')

# Force Sonar Reasoning Pro for deep analysis
research = ResearchLookup(force_model='reasoning')

# Automatic selection (default)
research = ResearchLookup()

Command-line usage:

# Force Sonar Pro Search
python research_lookup.py "your query" --force-model pro

# Force Sonar Reasoning Pro
python research_lookup.py "your query" --force-model reasoning

# Automatic (no flag)
python research_lookup.py "your query"

Technical Integration

OpenRouter API Configuration

This skill integrates with OpenRouter (openrouter.ai) to access Perplexity's Sonar models:

Model Specifications:

• Models:

- perplexity/sonar-pro-search (fast lookup)

- perplexity/sonar-reasoning-pro-online (deep analysis)

• Search Mode: Academic/scholarly mode (prioritizes peer-reviewed sources)
• Search Context: Always uses high search context for deeper, more comprehensive research results
• Context Window: 200K+ tokens for comprehensive research
• Capabilities: Academic paper search, citation generation, scholarly analysis
• Output: Rich responses with citations and source links from academic databases

API Requirements:

• OpenRouter API key (set as OPENROUTER_API_KEY environment variable)
• Account with sufficient credits for research queries
• Proper attribution and citation of sources

Academic Mode Configuration:

• System message configured to prioritize scholarly sources
• Search focused on peer-reviewed journals and academic publications
• Enhanced citation extraction for academic references
• Preference for recent academic literature (2020-2024)
• Direct access to academic databases and repositories

Response Quality and Reliability

Source Verification: The skill prioritizes:

• Peer-reviewed academic papers and journals
• Reputable institutional sources (universities, government agencies, NGOs)
• Recent publications (within last 2-3 years preferred)
• High-impact journals and conferences
• Primary research over secondary sources

Citation Standards: All responses include:

• Complete bibliographic information
• DOI or stable URLs when available
• Access dates for web sources
• Clear attribution of direct quotes or data

Query Best Practices

1. Model Selection Strategy

For Simple Lookups (Sonar Pro Search):

• Recent papers on a specific topic
• Statistical data or prevalence rates
• Standard protocols or methodologies
• Citation finding for specific papers
• Factual information retrieval

For Complex Analysis (Sonar Reasoning Pro):

• Comparative studies and synthesis
• Mechanism explanations
• Controversy evaluation
• Trade-off analysis
• Theoretical frameworks
• Multi-faceted relationships

Pro Tip: The automatic selection is optimized for most use cases. Only use force_model if you have specific requirements or know the query needs deeper reasoning than detected.

2. Specific and Focused Queries

Good Queries (will trigger appropriate model):

• "Randomized controlled trials of mRNA vaccines for cancer treatment 2023-2024" → Sonar Pro Search
• "Compare the efficacy and safety of mRNA vaccines vs traditional vaccines for cancer treatment" → Sonar Reasoning Pro
• "Explain the mechanism by which CRISPR off-target effects occur and strategies to minimize them" → Sonar Reasoning Pro

Poor Queries:

• "Tell me about AI" (too broad)
• "Cancer research" (lacks specificity)
• "Latest news" (too vague)

3. Structured Query Format

Recommended Structure:

[Topic] + [Specific Aspect] + [Time Frame] + [Type of Information]

Examples:

• "CRISPR gene editing + off-target effects + 2024 + clinical trials"
• "Quantum computing + error correction + recent advances + review papers"
• "Renewable