name	research-lookup
description	Look up current research information using Perplexity's Sonar Pro Search or Sonar Reasoning Pro models through OpenRouter. Automatically selects the best model based on query complexity. Search academic papers, recent studies, technical documentation, and general research information with citations.
allowed-tools	["Read","Write","Edit","Bash"]

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.

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 energy + solar efficiency + 2023-2024 + statistical data"

4. Follow-up Queries

Effective Follow-ups:

"Show me the full citation for the Smith et al. 2024 paper"
"What are the limitations of this methodology?"
"Find similar studies using different approaches"
"What controversies exist in this research area?"

Integration with Scientific Writing

This skill enhances scientific writing by providing:

Literature Review Support: Gather current research for introduction and discussion sections
Methods Validation: Verify protocols and procedures against current standards
Results Contextualization: Compare findings with recent similar studies
Discussion Enhancement: Support arguments with latest evidence
Citation Management: Provide properly formatted citations in multiple styles

Error Handling and Limitations

Known Limitations:

Information cutoff: Responses limited to training data (typically 2023-2024)
Paywall content: May not access full text behind paywalls
Emerging research: May miss very recent papers not yet indexed
Specialized databases: Cannot access proprietary or restricted databases

Error Conditions:

API rate limits or quota exceeded
Network connectivity issues
Malformed or ambiguous queries
Model unavailability or maintenance

Fallback Strategies:

Rephrase queries for better clarity
Break complex queries into simpler components
Use broader time frames if recent data unavailable
Cross-reference with multiple query variations

Usage Examples

Example 1: Simple Literature Search (Sonar Pro Search)

Query: "Recent advances in transformer attention mechanisms 2024"

Model Selected: Sonar Pro Search (straightforward lookup)

Response Includes:

Summary of 5 key papers from 2024
Complete citations with DOIs
Key innovations and improvements
Performance benchmarks
Future research directions

Example 2: Comparative Analysis (Sonar Reasoning Pro)

Query: "Compare and contrast the advantages and limitations of transformer-based models versus traditional RNNs for sequence modeling"

Model Selected: Sonar Reasoning Pro (complex analysis required)

Response Includes:

Detailed comparison across multiple dimensions
Analysis of architectural differences
Trade-offs in computational efficiency vs performance
Use case recommendations
Synthesis of evidence from multiple studies
Discussion of ongoing debates in the field

Example 3: Method Verification (Sonar Pro Search)

Query: "Standard protocols for flow cytometry analysis"

Model Selected: Sonar Pro Search (protocol lookup)

Response Includes:

Step-by-step protocol from recent review
Required controls and calibrations
Common pitfalls and troubleshooting
Reference to definitive methodology paper
Alternative approaches with pros/cons

Example 4: Mechanism Explanation (Sonar Reasoning Pro)

Query: "Explain the underlying mechanism of how mRNA vaccines trigger immune responses and why they differ from traditional vaccines"

Model Selected: Sonar Reasoning Pro (requires causal reasoning)

Response Includes:

Detailed mechanistic explanation
Step-by-step biological processes
Comparative analysis with traditional vaccines
Molecular-level interactions
Integration of immunology and pharmacology concepts
Evidence from recent research

Example 5: Statistical Data (Sonar Pro Search)

Query: "Global AI adoption in healthcare statistics 2024"

Model Selected: Sonar Pro Search (data lookup)

Response Includes:

Current adoption rates by region
Market size and growth projections
Survey methodology and sample size
Comparison with previous years
Citations to market research reports

Performance and Cost Considerations

Response Times

Sonar Pro Search:

Typical response time: 5-15 seconds
Best for rapid information gathering
Suitable for batch queries

Sonar Reasoning Pro:

Typical response time: 15-45 seconds
Worth the wait for complex analytical queries
Provides more thorough reasoning and synthesis

Cost Optimization

Automatic Selection Benefits:

Saves costs by using Sonar Pro Search for straightforward queries
Reserves Sonar Reasoning Pro for queries that truly benefit from deeper analysis
Optimizes the balance between cost and quality

Manual Override Use Cases:

Force Sonar Pro Search when budget is constrained and speed is priority
Force Sonar Reasoning Pro when working on critical research requiring maximum depth
Use for specific sections of papers (e.g., Pro Search for methods, Reasoning for discussion)

Best Practices:

Trust the automatic selection for most use cases
Review query results - if Sonar Pro Search doesn't provide sufficient depth, rephrase with reasoning keywords
Use batch queries strategically - combine simple lookups to minimize total query count
For literature reviews, start with Sonar Pro Search for breadth, then use Sonar Reasoning Pro for synthesis

Security and Ethical Considerations

Responsible Use:

Verify all information against primary sources when possible
Clearly attribute all data and quotes to original sources
Avoid presenting AI-generated summaries as original research
Respect copyright and licensing restrictions
Use for research assistance, not to bypass paywalls or subscriptions

Academic Integrity:

Always cite original sources, not the AI tool
Use as a starting point for literature searches
Follow institutional guidelines for AI tool usage
Maintain transparency about research methods

Complementary Tools

In addition to research-lookup, the scientific writer has access to WebSearch for:

Quick metadata verification: Look up DOIs, publication years, journal names, volume/page numbers
Non-academic sources: News, blogs, technical documentation, current events
General information: Company info, product details, current statistics
Cross-referencing: Verify citation details found through research-lookup

When to use which tool:

Task	Tool
Find academic papers	research-lookup
Literature search	research-lookup
Deep analysis/comparison	research-lookup (Sonar Reasoning Pro)
Look up DOI/metadata	WebSearch
Verify publication year	WebSearch
Find journal volume/pages	WebSearch
Current events/news	WebSearch
Non-scholarly sources	WebSearch

Summary

This skill serves as a powerful research assistant with intelligent dual-model selection:

Automatic Intelligence: Analyzes query complexity and selects the optimal model (Sonar Pro Search or Sonar Reasoning Pro)
Cost-Effective: Uses faster, cheaper Sonar Pro Search for straightforward lookups
Deep Analysis: Automatically engages Sonar Reasoning Pro for complex comparative, analytical, and theoretical queries
Flexible Control: Manual override available when you know exactly what level of analysis you need
Academic Focus: Both models configured to prioritize peer-reviewed sources and scholarly literature
Complementary WebSearch: Use alongside WebSearch for metadata verification and non-academic sources

Whether you need quick fact-finding or deep analytical synthesis, this skill automatically adapts to deliver the right level of research support for your scientific writing needs.

name	research-lookup
description	Look up current research information using Perplexity's Sonar Pro Search or Sonar Reasoning Pro models through OpenRouter. Automatically selects the best model based on query complexity. Search academic papers, recent studies, technical documentation, and general research information with citations.
allowed-tools	["Read","Write","Edit","Bash"]

Research Information Lookup

Overview

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.

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 energy + solar efficiency + 2023-2024 + statistical data"

4. Follow-up Queries

Effective Follow-ups:

"Show me the full citation for the Smith et al. 2024 paper"
"What are the limitations of this methodology?"
"Find similar studies using different approaches"
"What controversies exist in this research area?"

Integration with Scientific Writing

This skill enhances scientific writing by providing:

Literature Review Support: Gather current research for introduction and discussion sections
Methods Validation: Verify protocols and procedures against current standards
Results Contextualization: Compare findings with recent similar studies
Discussion Enhancement: Support arguments with latest evidence
Citation Management: Provide properly formatted citations in multiple styles

Error Handling and Limitations

Known Limitations:

Information cutoff: Responses limited to training data (typically 2023-2024)
Paywall content: May not access full text behind paywalls
Emerging research: May miss very recent papers not yet indexed
Specialized databases: Cannot access proprietary or restricted databases

Error Conditions:

API rate limits or quota exceeded
Network connectivity issues
Malformed or ambiguous queries
Model unavailability or maintenance

Fallback Strategies:

Rephrase queries for better clarity
Break complex queries into simpler components
Use broader time frames if recent data unavailable
Cross-reference with multiple query variations

Usage Examples

Example 1: Simple Literature Search (Sonar Pro Search)

Query: "Recent advances in transformer attention mechanisms 2024"

Model Selected: Sonar Pro Search (straightforward lookup)

Response Includes:

Summary of 5 key papers from 2024
Complete citations with DOIs
Key innovations and improvements
Performance benchmarks
Future research directions

Example 2: Comparative Analysis (Sonar Reasoning Pro)

Query: "Compare and contrast the advantages and limitations of transformer-based models versus traditional RNNs for sequence modeling"

Model Selected: Sonar Reasoning Pro (complex analysis required)

Response Includes:

Detailed comparison across multiple dimensions
Analysis of architectural differences
Trade-offs in computational efficiency vs performance
Use case recommendations
Synthesis of evidence from multiple studies
Discussion of ongoing debates in the field

Example 3: Method Verification (Sonar Pro Search)

Query: "Standard protocols for flow cytometry analysis"

Model Selected: Sonar Pro Search (protocol lookup)

Response Includes:

Step-by-step protocol from recent review
Required controls and calibrations
Common pitfalls and troubleshooting
Reference to definitive methodology paper
Alternative approaches with pros/cons

Example 4: Mechanism Explanation (Sonar Reasoning Pro)

Query: "Explain the underlying mechanism of how mRNA vaccines trigger immune responses and why they differ from traditional vaccines"

Model Selected: Sonar Reasoning Pro (requires causal reasoning)

Response Includes:

Detailed mechanistic explanation
Step-by-step biological processes
Comparative analysis with traditional vaccines
Molecular-level interactions
Integration of immunology and pharmacology concepts
Evidence from recent research

Example 5: Statistical Data (Sonar Pro Search)

Query: "Global AI adoption in healthcare statistics 2024"

Model Selected: Sonar Pro Search (data lookup)

Response Includes:

Current adoption rates by region
Market size and growth projections
Survey methodology and sample size
Comparison with previous years
Citations to market research reports

Performance and Cost Considerations

Response Times

Sonar Pro Search:

Typical response time: 5-15 seconds
Best for rapid information gathering
Suitable for batch queries

Sonar Reasoning Pro:

Typical response time: 15-45 seconds
Worth the wait for complex analytical queries
Provides more thorough reasoning and synthesis

Cost Optimization

Automatic Selection Benefits:

Saves costs by using Sonar Pro Search for straightforward queries
Reserves Sonar Reasoning Pro for queries that truly benefit from deeper analysis
Optimizes the balance between cost and quality

Manual Override Use Cases:

Force Sonar Pro Search when budget is constrained and speed is priority
Force Sonar Reasoning Pro when working on critical research requiring maximum depth
Use for specific sections of papers (e.g., Pro Search for methods, Reasoning for discussion)

Best Practices:

Trust the automatic selection for most use cases
Review query results - if Sonar Pro Search doesn't provide sufficient depth, rephrase with reasoning keywords
Use batch queries strategically - combine simple lookups to minimize total query count
For literature reviews, start with Sonar Pro Search for breadth, then use Sonar Reasoning Pro for synthesis

Security and Ethical Considerations

Responsible Use:

Verify all information against primary sources when possible
Clearly attribute all data and quotes to original sources
Avoid presenting AI-generated summaries as original research
Respect copyright and licensing restrictions
Use for research assistance, not to bypass paywalls or subscriptions

Academic Integrity:

Always cite original sources, not the AI tool
Use as a starting point for literature searches
Follow institutional guidelines for AI tool usage
Maintain transparency about research methods

Complementary Tools

In addition to research-lookup, the scientific writer has access to WebSearch for:

Quick metadata verification: Look up DOIs, publication years, journal names, volume/page numbers
Non-academic sources: News, blogs, technical documentation, current events
General information: Company info, product details, current statistics
Cross-referencing: Verify citation details found through research-lookup

When to use which tool:

Task	Tool
Find academic papers	research-lookup
Literature search	research-lookup
Deep analysis/comparison	research-lookup (Sonar Reasoning Pro)
Look up DOI/metadata	WebSearch
Verify publication year	WebSearch
Find journal volume/pages	WebSearch
Current events/news	WebSearch
Non-scholarly sources	WebSearch

Summary

This skill serves as a powerful research assistant with intelligent dual-model selection:

Automatic Intelligence: Analyzes query complexity and selects the optimal model (Sonar Pro Search or Sonar Reasoning Pro)
Cost-Effective: Uses faster, cheaper Sonar Pro Search for straightforward lookups
Deep Analysis: Automatically engages Sonar Reasoning Pro for complex comparative, analytical, and theoretical queries
Flexible Control: Manual override available when you know exactly what level of analysis you need
Academic Focus: Both models configured to prioritize peer-reviewed sources and scholarly literature
Complementary WebSearch: Use alongside WebSearch for metadata verification and non-academic sources

Whether you need quick fact-finding or deep analytical synthesis, this skill automatically adapts to deliver the right level of research support for your scientific writing needs.