literature-search

yorkeccak/scientific-skills · updated Apr 8, 2026

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$npx skills add https://github.com/yorkeccak/scientific-skills --skill literature-search
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summary

Search across all major scientific literature databases (PubMed, arXiv, bioRxiv, medRxiv) simultaneously using natural language queries powered by Valyu's semantic search API.

skill.md

Literature Search

Search across all major scientific literature databases (PubMed, arXiv, bioRxiv, medRxiv) simultaneously using natural language queries powered by Valyu's semantic search API.

Why This Skill is Powerful

  • No API Parameter Parsing: Just pass natural language queries directly - no need to construct complex search parameters
  • Semantic Search: Understands the meaning of your query, not just keyword matching
  • Full-Text Access: Returns complete article content, not just abstracts
  • Image Links: Includes figures and images from papers
  • Comprehensive Coverage: Search across PubMed, arXiv, bioRxiv, and medRxiv simultaneously
  • Unified Results: Get results from all sources in a single query

Requirements

  1. Node.js 18+ (uses built-in fetch)
  2. Valyu API key from https://platform.valyu.ai ($10 free credits)

CRITICAL: Script Path Resolution

The scripts/search commands in this documentation are relative to this skill's installation directory.

Before running any command, locate the script using:

LITERATURE_SCRIPT=$(find ~/.claude/plugins/cache -name "search" -path "*/literature-search/*/scripts/*" -type f 2>/dev/null | head -1)

Then use the full path for all commands:

$LITERATURE_SCRIPT "CRISPR gene editing advances" 15

API Key Setup Flow

When you run a search and receive "setup_required": true, follow this flow:

  1. Ask the user for their API key: "To search scientific literature, I need your Valyu API key. Get one free ($10 credits) at https://platform.valyu.ai"

  2. Once the user provides the key, run:

    scripts/search setup <api-key>
    
  3. Retry the original search.

When to Use This Skill

  • Comprehensive literature reviews across all domains
  • Finding all relevant research on a topic
  • Cross-domain scientific discovery
  • Combining biomedical, physics, and preprint literature
  • Emerging research across disciplines

Output Format

{
  "success": true,
  "type": "literature_search",
  "query": "CRISPR gene editing advances",
  "result_count": 15,
  "results": [
    {
      "title": "Article Title",
      "url": "https://...",
      "content": "Full article text with figures...",
      "source": "pubmed|arxiv|biorxiv|medrxiv",
      "relevance_score": 0.95,
      "images": ["https://example.com/figure1.jpg"]
    }
  ],
  "cost": 0.025
}

Processing Results

With jq

# Get article titles
scripts/search "query" 20 | jq -r '.results[].title'

# Get URLs
scripts/search "query" 20 | jq -r '.results[].url'

# Extract full content
scripts/search "query" 20 | jq -r '.results[].content'

# Filter by source
scripts/search "query" 20 | jq -r '.results[] | select(.source == "arxiv") | .title'

Common Use Cases

Comprehensive Literature Review

# Search across all sources for thorough review
scripts/search "mechanisms of cellular senescence" 100

Cross-Disciplinary Research

# Find papers spanning multiple fields
scripts/search "quantum computing applications in drug discovery" 50

Recent Developments

# Get latest preprints and publications
scripts/search "foundation models for protein folding" 30

Medical Research

# Search biomedical literature comprehensively
scripts/search "immunotherapy checkpoint inhibitors resistance" 40

Error Handling

All commands return JSON with success field:

{
  "success": false,
  "error": "Error message"
}

Exit codes:

  • 0 - Success
  • 1 - Error (check JSON for details)

API Endpoint

  • Base URL: https://api.valyu.ai/v1
  • Endpoint: /search
  • Authentication: X-API-Key header

Architecture

scripts/
├── search          # Bash wrapper
└── search.mjs      # Node.js CLI

Direct API calls using Node.js built-in fetch(), zero external dependencies.

Adding to Your Project

If you're building an AI project and want to integrate Literature Search directly into your application, use the Valyu SDK:

Python Integration

from valyu import Valyu

client = Valyu(api_key="your-api-key")

response = client.search(
    query="your search query here",
    included_sources=["valyu/valyu-pubmed", "valyu/valyu-arxiv", "valyu/valyu-biorxiv", "valyu/valyu-medrxiv"],
    max_results=20
)

for result in response["results"]:
    print(f"Title: {result['title']}")
    print(f"URL: {result['url']}")
    print(f"Content: {result['content'][:500]}...")

TypeScript Integration

import { Valyu } from "valyu-js";

const client = new Valyu("your-api-key");

const response = await client.search({
  query: "your search query here",
  includedSources: ["valyu/valyu-pubmed", "valyu/valyu-arxiv", "valyu/valyu-biorxiv", "valyu/valyu-medrxiv"],
  maxResults: 20
});

response.results.forEach((result) => {
  console.log(`Title: ${result.title}`);
  console.log(`URL: ${result.url}`);
  console.log(`Content: ${result.content.substring(0, 500)}...`);
});

See the Valyu docs for full integration examples and SDK reference.

how to use literature-search

How to use literature-search 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 literature-search
2

Execute installation command

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

$npx skills add https://github.com/yorkeccak/scientific-skills --skill literature-search

The skills CLI fetches literature-search from GitHub repository yorkeccak/scientific-skills 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/literature-search

Reload or restart Cursor to activate literature-search. Access the skill through slash commands (e.g., /literature-search) 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.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

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)
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general reviews

Ratings

4.832 reviews
  • Pratham Ware· Dec 28, 2024

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

  • Chaitanya Patil· Dec 24, 2024

    We added literature-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Isabella Menon· Dec 8, 2024

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

  • Hassan Chawla· Nov 27, 2024

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

  • Piyush G· Nov 15, 2024

    literature-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Meera Malhotra· Oct 18, 2024

    literature-search is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Shikha Mishra· Oct 6, 2024

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

  • Fatima Ramirez· Sep 5, 2024

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

  • Aditi Kim· Aug 24, 2024

    Keeps context tight: literature-search is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aditi Mensah· Jul 15, 2024

    literature-search is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

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