Reorganize: Move all skills to skills/ folder
- Created skills/ directory - Moved 272 skills to skills/ subfolder - Kept agents/ at root level - Kept installation scripts and docs at root level Repository structure: - skills/ - All 272 skills from skills.sh - agents/ - Agent definitions - *.sh, *.ps1 - Installation scripts - README.md, etc. - Documentation Co-Authored-By: Claude <noreply@anthropic.com>
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skills/arxiv-search/skill.md
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skills/arxiv-search/skill.md
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name: arxiv-search
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description: Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
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keywords:
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- arxiv
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- preprints
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- physics
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- mathematics
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- computer-science
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- ai-research
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- semantic-search
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license: MIT
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---
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# arXiv Search
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Search the complete arXiv database of preprints across physics, mathematics, computer science, and quantitative biology using natural language queries powered by Valyu's semantic search API.
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## Why This Skill is Powerful
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- **No API Parameter Parsing**: Just pass natural language queries directly - no need to construct complex search parameters
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- **Semantic Search**: Understands the meaning of your query, not just keyword matching
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- **Full-Text Access**: Returns complete article content, not just abstracts
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- **Image Links**: Includes figures and images from papers
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- **Comprehensive Coverage**: Access to all of arXiv's preprint archive across multiple disciplines
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## Requirements
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1. Node.js 18+ (uses built-in fetch)
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2. Valyu API key from https://platform.valyu.ai ($10 free credits)
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## CRITICAL: Script Path Resolution
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The `scripts/search` commands in this documentation are relative to this skill's installation directory.
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Before running any command, locate the script using:
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```bash
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ARXIV_SCRIPT=$(find ~/.claude/plugins/cache -name "search" -path "*/arxiv-search/*/scripts/*" -type f 2>/dev/null | head -1)
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```
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Then use the full path for all commands:
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```bash
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$ARXIV_SCRIPT "quantum entanglement" 15
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```
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## API Key Setup Flow
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When you run a search and receive `"setup_required": true`, follow this flow:
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1. **Ask the user for their API key:**
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"To search arXiv, I need your Valyu API key. Get one free ($10 credits) at https://platform.valyu.ai"
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2. **Once the user provides the key, run:**
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```bash
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scripts/search setup <api-key>
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```
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3. **Retry the original search.**
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### Example Flow:
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```
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User: Search arXiv for transformer architecture papers
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→ Response: {"success": false, "setup_required": true, ...}
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→ Claude asks: "Please provide your Valyu API key from https://platform.valyu.ai"
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→ User: "val_abc123..."
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→ Claude runs: scripts/search setup val_abc123...
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→ Response: {"success": true, "type": "setup", ...}
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→ Claude retries: scripts/search "transformer architecture papers" 10
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→ Success!
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```
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## When to Use This Skill
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- Searching preprints across physics, mathematics, and computer science
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- Finding research before peer review publication
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- Cross-disciplinary research combining fields
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- Staying current with rapid developments in AI and theoretical physics
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- Prior art searching for new ideas
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- Tracking emerging research trends
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## Output Format
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```json
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{
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"success": true,
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"type": "arxiv_search",
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"query": "quantum entanglement",
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"result_count": 10,
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"results": [
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{
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"title": "Article Title",
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"url": "https://arxiv.org/abs/...",
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"content": "Full article text with figures...",
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"source": "arxiv",
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"relevance_score": 0.95,
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"images": ["https://example.com/figure1.jpg"]
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}
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],
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"cost": 0.025
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}
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```
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## Processing Results
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### With jq
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```bash
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# Get article titles
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scripts/search "query" 10 | jq -r '.results[].title'
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# Get URLs
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scripts/search "query" 10 | jq -r '.results[].url'
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# Extract full content
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scripts/search "query" 10 | jq -r '.results[].content'
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```
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## Common Use Cases
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### AI/ML Research
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```bash
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# Find recent machine learning papers
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scripts/search "large language model architectures" 50
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```
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### Physics Research
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```bash
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# Search for quantum physics papers
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scripts/search "topological quantum computation" 20
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```
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### Mathematics
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```bash
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# Find math papers
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scripts/search "representation theory and Lie algebras" 15
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```
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### Computer Science
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```bash
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# Search for CS theory papers
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scripts/search "distributed systems consensus algorithms" 25
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```
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## Error Handling
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All commands return JSON with `success` field:
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```json
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{
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"success": false,
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"error": "Error message"
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}
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```
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Exit codes:
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- `0` - Success
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- `1` - Error (check JSON for details)
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## API Endpoint
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- Base URL: `https://api.valyu.ai/v1`
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- Endpoint: `/search`
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- Authentication: X-API-Key header
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## Architecture
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```
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scripts/
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├── search # Bash wrapper
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└── search.mjs # Node.js CLI
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```
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Direct API calls using Node.js built-in `fetch()`, zero external dependencies.
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## Adding to Your Project
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If you're building an AI project and want to integrate arXiv Search directly into your application, use the Valyu SDK:
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### Python Integration
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```python
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from valyu import Valyu
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client = Valyu(api_key="your-api-key")
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response = client.search(
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query="your search query here",
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included_sources=["valyu/valyu-arxiv"],
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max_results=20
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)
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for result in response["results"]:
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print(f"Title: {result['title']}")
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print(f"URL: {result['url']}")
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print(f"Content: {result['content'][:500]}...")
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```
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### TypeScript Integration
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```typescript
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import { Valyu } from "valyu-js";
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const client = new Valyu("your-api-key");
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const response = await client.search({
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query: "your search query here",
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includedSources: ["valyu/valyu-arxiv"],
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maxResults: 20
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});
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response.results.forEach((result) => {
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console.log(`Title: ${result.title}`);
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console.log(`URL: ${result.url}`);
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console.log(`Content: ${result.content.substring(0, 500)}...`);
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});
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```
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See the [Valyu docs](https://docs.valyu.ai) for full integration examples and SDK reference.
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