Agent skill

Research Lookup

by davila7 in davila7/claude-code-templates

Look up current research information using Perplexity's Sonar Pro Search or Sonar Reasoning Pro models through OpenRouter.

MITAuto-check: notesResearch & Science

Install Research Lookup

skills CLI
$ npx skills add davila7/claude-code-templates --skill research-lookup -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davila7/claude-code-templates research-lookup --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/scientific/research-lookup .claude/skills/research-lookup && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
research-lookup
GitHub stars
33k
Used in
9 other repos
Token cost
~5k tokens
SKILL.md length
2,131 words
Files
6 (incl. scripts)
Skills in repo
479
Repo updated
First seen
Licence
MIT

At a glance

Look up current research information using Perplexity's Sonar Pro Search or Sonar Reasoning Pro models through OpenRouter.

  • Works in 8 steps: Academic Research Queries → Technical and Methodological Information → Statistical and Data Information → …
  • Tasks that involve Academic paper search
  • SKILL.md covers Overview, When to Use This Skill, Visual Enhancement with… and Core Capabilities, plus 7 more sections
  • Runs Python scripts from its folder; calls python; needs OPENROUTER_API_KEY

What it does

Research Lookup is an agent skill from davila7/claude-code-templates. 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.

Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts (for example `README.md`, `examples.py` and `lookup.py`).

It sits in Research & Science, covering Academic paper search, Technical documentation and Model routing and gateways. It works with OpenRouter and Perplexity. The repository describes itself as: CLI tool for configuring and monitoring Claude Code. The licence is MIT.

When your agent uses it

  • Tasks that involve Academic paper search
  • Tasks that involve Technical documentation
  • Tasks that involve Model routing and gateways

Example prompts

  • “/research-lookup”

Requirements

  • Python 3
  • A credential in OPENROUTER_API_KEY
  • Pre-approved tools (allowed-tools): Read, Write, Edit, Bash

Workflow steps

8 steps, taken from the step headings in SKILL.md.

  1. Academic Research Queries
  2. Technical and Methodological Information
  3. Statistical and Data Information
  4. Citation and Reference Assistance
  5. Model Selection Strategy
  6. Specific and Focused Queries
  7. Structured Query Format
  8. Follow-up Queries

What it can do on your machine

Read from SKILL.md and the folder at commit 79182c5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • OPENROUTER_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Research Lookup loads about 5k tokens when it runs. Until then it costs about 79 tokens; SKILL.md has 2,131 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~79
When it runs · the whole SKILL.md, loaded when a task matches
~5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Read, Write, Edit, Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from davila7/claude-code-templates at commit 79182c5, republished under its MIT licence (© davila7). 2,131 words, ~4,965 tokens.

Download SKILL.mdSave it as .claude/skills/research-lookup/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
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:

bash
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:

python
# 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:

bash
# 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?"
Show full SKILL.md (869 more words)Show less

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

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

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

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
  • 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:

TaskTool
Find academic papersresearch-lookup
Literature searchresearch-lookup
Deep analysis/comparisonresearch-lookup (Sonar Reasoning Pro)
Look up DOI/metadataWebSearch
Verify publication yearWebSearch
Find journal volume/pagesWebSearch
Current events/newsWebSearch
Non-scholarly sourcesWebSearch

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.

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files (scripts) in cli-tool/components/skills/scientific/research-lookup of davila7/claude-code-templates.

  • SKILL.md
  • README.md
  • examples.py
  • lookup.py
  • research_lookup.py
  • scripts/research_lookup.py

Open the folder on GitHubat commit 79182c5

Used in 9 other repositories

We found 11 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 9 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Research Lookup next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Research Lookup compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Research Lookup this skilldavila7/claude-code-templates33k9 repos~5kAutomated safety check: NotesMIT
Literature Review AgentAr9av/PaperOrchestra6791 repos~5.2kAutomated safety check: PassCustom licence
Survey Generatorrohitg00/pro-workflow2.9k—~1.6kAutomated safety check: PassNone
Research Lookupneflibata-feng/MyArxiv-Agent1262 repos~4.1kAutomated safety check: NotesMIT
Weekly Signal DiffNateBJones-Projects/OB14.7k—~1.7kAutomated safety check: PassCustom licence
Update Video SurveyLJungang/Awesome-Video-Reasoning-Landscape193—~1.6kAutomated safety check: PassNone

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Questions about Research Lookup

What does Research Lookup do?

Look up current research information using Perplexity's Sonar Pro Search or Sonar Reasoning Pro models through OpenRouter. Research Lookup is an agent skill from davila7/claude-code-templates. Look up current research information using Perplexity's Sonar Pro Search or Sonar Reasoning Pro models through OpenRouter.

When should I use Research Lookup?

Research Lookup fits situations like: tasks that involve Academic paper search; tasks that involve Technical documentation; tasks that involve Model routing and gateways.

How do I install Research Lookup in Claude Code?

Run `npx skills add davila7/claude-code-templates --skill research-lookup -a claude-code`. Or copy the skill folder (cli-tool/components/skills/scientific/research-lookup in davila7/claude-code-templates) into .claude/skills/research-lookup in your project. Claude Code loads it when a task matches its description.

How do I install Research Lookup in Codex?

Run `npx skills add davila7/claude-code-templates --skill research-lookup -a codex`. Or copy the skill folder (cli-tool/components/skills/scientific/research-lookup in davila7/claude-code-templates) into .agents/skills/research-lookup in your project. Codex loads it when a task matches its description.

Can I use Research Lookup in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davila7/claude-code-templates --skill research-lookup -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/research-lookup, .gemini/skills/research-lookup, .github/skills/research-lookup and .opencode/skills/research-lookup in your project.

What does Research Lookup need to run?

Going by SKILL.md and its folder, Research Lookup needs Python for the scripts in its folder, the command-line tools its instructions call (python) and credentials named OPENROUTER_API_KEY. Our summary lists: Python 3; A credential in OPENROUTER_API_KEY. Its frontmatter pre-approves these tools: Read, Write, Edit, Bash.

Does Research Lookup access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Research Lookup safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Research Lookup use?

Research Lookup is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Research Lookup use?

About 5k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Research Lookup?

Skills that share tags, products or a category with Research Lookup: Literature Review Agent (Ar9av/PaperOrchestra, 679 stars), Survey Generator (rohitg00/pro-workflow, 2.9k stars), Research Lookup (neflibata-feng/MyArxiv-Agent, 126 stars) and Weekly Signal Diff (NateBJones-Projects/OB1, 4.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Research Lookup?

davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,552 GitHub stars. The repository holds 479 skills in this directory. The repository was last updated on October 11, 2026.

Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.