research-lookup

davila7/claude-code-templates · updated Apr 8, 2026

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$npx skills add https://github.com/davila7/claude-code-templates --skill research-lookup
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summary

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.

skill.md

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:

  1. Literature Review Support: Gather current research for introduction and discussion sections
  2. Methods Validation: Verify protocols and procedures against current standards
  3. Results Contextualization: Compare findings with recent similar studies
  4. Discussion Enhancement: Support arguments with latest evidence
  5. 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:

  1. Trust the automatic selection for most use cases
  2. Review query results - if Sonar Pro Search doesn't provide sufficient depth, rephrase with reasoning keywords
  3. Use batch queries strategically - combine simple lookups to minimize total query count
  4. 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
  • Respec
how to use research-lookup

How to use research-lookup on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add research-lookup
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/davila7/claude-code-templates --skill research-lookup

The skills CLI fetches research-lookup from GitHub repository davila7/claude-code-templates and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/research-lookup

Reload or restart Cursor to activate research-lookup. Access the skill through slash commands (e.g., /research-lookup) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.825 reviews
  • Chen Yang· Dec 28, 2024

    I recommend research-lookup for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Aanya Torres· Nov 19, 2024

    Solid pick for teams standardizing on skills: research-lookup is focused, and the summary matches what you get after install.

  • Aditi Jain· Oct 10, 2024

    research-lookup has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Sakshi Patil· Sep 25, 2024

    I recommend research-lookup for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chaitanya Patil· Aug 16, 2024

    Useful defaults in research-lookup — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Rahul Santra· Jul 15, 2024

    Registry listing for research-lookup matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aditi Rahman· Jul 15, 2024

    research-lookup reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Piyush G· Jul 7, 2024

    research-lookup has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Shikha Mishra· Jun 26, 2024

    Solid pick for teams standardizing on skills: research-lookup is focused, and the summary matches what you get after install.

  • Harper Okafor· Jun 22, 2024

    Solid pick for teams standardizing on skills: research-lookup is focused, and the summary matches what you get after install.

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