patents-search

Search the complete global patent database using natural language queries powered by Valyu's semantic search API.

yorkeccak/scientific-skillsUpdated Apr 8, 2026

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Install Skill

Run in your terminal

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

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Installation Guide

How to use patents-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 machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add patents-search
2

Run the install 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 patents-search

Fetches patents-search from yorkeccak/scientific-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/patents-search

Restart Cursor to activate patents-search. Access via /patents-search in your agent's command palette.

Security 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 environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

Patents Search

Search the complete global patent database 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 patent information including claims, descriptions, and technical details
  • Image Links: Includes patent diagrams and figures when available
  • Comprehensive Coverage: Access to global patent data across jurisdictions

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:

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

Then use the full path for all commands:

$PATENTS_SCRIPT "CRISPR gene editing methods" 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 patents, 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

  • Prior art searching and patent landscaping
  • Technology trend analysis
  • Competitor innovation tracking
  • Patent freedom-to-operate analysis
  • Patent claim analysis and interpretation
  • Patent filing strategy research

Output Format

{
  "success": true,
  "type": "patents_search",
  "query": "CRISPR gene editing methods",
  "result_count": 10,
  "results": [
    {
      "title": "Patent Title",
      "url": "https://patents.google.com/...",
      "content": "Patent claims, description, technical details...",
      "source": "patents",
      "relevance_score": 0.95,
      "images": ["https://example.com/diagram.png"]
    }
  ],
  "cost": 0.025
}

Processing Results

With jq

# Get patent titles
scripts/search "query" 10 | jq -r '.results[].title'

# Get URLs
scripts/search "query" 10 | jq -r '.results[].url'

# Extract full content
scripts/search "query" 10 | jq -r '.results[].content'

Common Use Cases

Prior Art Search

# Find prior art
scripts/search "lithium ion battery electrode materials" 50

Competitive Intelligence

# Search competitor patents
scripts/search "CAR-T cell therapy manufacturing methods" 20

Technology Landscape

# Find technology trends
scripts/search "quantum computing error correction patents" 15

Freedom to Operate

# Search for blocking patents
scripts/search "mRNA vaccine delivery systems" 25

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 Patents 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-patents"],
    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-patents"],
  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.

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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

Steps

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

Related Skills

Reviews

4.648 reviews
  • P
    Pratham WareDec 28, 2024

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

  • R
    Ren SanchezDec 24, 2024

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

  • M
    Min ChenDec 24, 2024

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

  • S
    Sofia GonzalezDec 12, 2024

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

  • S
    Sakura FarahDec 8, 2024

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

  • A
    Aditi SinghNov 27, 2024

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

  • Y
    Yash ThakkerNov 19, 2024

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

  • M
    Mateo MartinNov 15, 2024

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

  • A
    Amelia MartinNov 3, 2024

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

  • M
    Mateo HarrisNov 3, 2024

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

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