| name | deepxiv-cli |
| version | 0.2.0 |
| description | Access academic papers (arXiv, PMC, and coming soon bioRxiv, medRxiv) via CLI with hybrid search and intelligent content extraction |
| frameworks | ["codex","langchain","claude-code","custom-agents"] |
| use_cases | ["literature-search","paper-analysis","knowledge-synthesis","research-assistant"] |
DeepXiv CLI Skill
🚀 30-Second Overview
What: Access open access academic papers (arXiv, PMC, bioRxiv, medRxiv) through a powerful CLI tool.
What you can do:
- 🔍 Search papers with hybrid search (BM25 + Vector)
- 📄 Read papers section-by-section (save tokens!)
- 🧠 Use built-in AI agent for analysis
- 📊 Access biomedical literature (PMC)
When to use: User wants to search, read, or analyze academic papers
🎯 Command Selection Guide
I want to... → Use this command
| Goal | Command | Example |
|---|
| Find papers on a topic | deepxiv search | deepxiv search "agent memory" --limit 5 |
| Quickly understand a paper | deepxiv paper <id> --brief | deepxiv paper 2409.05591 --brief |
| Read specific section | deepxiv paper <id> --section | deepxiv paper 2409.05591 --section Introduction |
| See paper structure | deepxiv paper <id> --head | deepxiv paper 2409.05591 --head |
| Preview first 10k chars | deepxiv paper <id> --preview | deepxiv paper 2409.05591 --preview |
| Get full text | deepxiv paper <id> | deepxiv paper 2409.05591 |
| Access biomedical paper | deepxiv pmc <id> | deepxiv pmc PMC544940 |
| Intelligent analysis | deepxiv agent query | deepxiv agent query "analyze this paper" |
📚 Core Commands Reference
1. Search Papers (deepxiv search)
When to use: Finding relevant papers on a topic
deepxiv search "agent memory" --limit 5
deepxiv search "transformer" --mode bm25 --format json
deepxiv search "LLM" --categories cs.AI,cs.CL --min-citations 100
deepxiv search "vision models" --date-from 2024-01-01 --date-to 2024-12-31
Expected output: List of papers with title, arxiv_id, score, citation count
Token cost: ~500-1000 tokens per search
Tips:
- Use
--limit 3-5 for quick overview
- Use
--format json for downstream processing
- Adjust
bm25_weight and vector_weight for different search styles
2. Read arXiv Papers (deepxiv paper)
When to use: Understanding specific papers (choose format by depth needed)
Option A: Quick Summary (30 seconds)
deepxiv paper 2409.05591 --brief
Option B: Paper Structure (2 minutes)
deepxiv paper 2409.05591 --head
Option C: Quick Scan (3 minutes)
deepxiv paper 2409.05591 --preview
Option D: Specific Section (1 minute)
deepxiv paper 2409.05591 --section Introduction
Option E: Complete Paper (for deep analysis)
deepxiv paper 2409.05591
3. Access Biomedical Literature (deepxiv pmc)
When to use: Need medical, biology, or biomedical research
deepxiv pmc PMC544940 --head
deepxiv pmc PMC544940
Expected output: Paper metadata or complete paper JSON
Token cost: ~1-2k tokens (metadata), ~10-30k tokens (full)
4. Manage Token (deepxiv token)
When to use: Check your API token status
deepxiv token
Note: Token auto-registers on first use, saves to ~/.env
5. Intelligent Agent (deepxiv agent)
When to use: Need analysis beyond simple retrieval
deepxiv agent query "What are key innovations in this paper?"
deepxiv agent query "Compare these two approaches" --max-turn 10 --verbose
deepxiv agent config
Token cost: Varies by reasoning depth
Requirements: Requires langgraph and langchain-core
🎬 Common Workflows
Workflow 1: Quick Paper Review (2 minutes)
deepxiv paper 2409.05591 --brief
deepxiv paper 2409.05591 --section Introduction
deepxiv paper 2409.05591 --section Results
Total tokens: ~2-3k | Use case: Quick assessment before deciding to read fully
Workflow 2: Deep Paper Analysis (15 minutes)
deepxiv paper 2409.05591 --head
deepxiv paper 2409.05591 --section Introduction
deepxiv paper 2409.05591 --section Methods
deepxiv paper 2409.05591 --section Results
deepxiv agent query "Summarize the main contributions"
Total tokens: ~10-15k | Use case: Thorough understanding
Workflow 3: Literature Search (5 minutes)
deepxiv search "agent memory" --limit 5
for id in results; do
deepxiv paper $id --brief
done
deepxiv paper <top_id_1>
deepxiv paper <top_id_2>
Total tokens: ~5-10k | Use case: Literature review
💪 Capabilities & Limitations
What deepxiv Can Do ✅
| Capability | Details |
|---|
| Hybrid Search | BM25 + Vector search across 2M+ arXiv papers |
| Smart Summaries | AI-generated TLDRs and keywords |
| Section Access | Read specific sections without loading full text |
| Biomedical Access | PubMed Central (PMC) papers |
| Open Access Only | arXiv, PMC, bioRxiv (coming), medRxiv (coming) |
| Intelligent Analysis | ReAct agent with multi-turn reasoning |
| Multiple LLMs | Compatible with OpenAI, DeepSeek, OpenRouter, etc. |
What deepxiv Cannot Do ❌
| Limitation | Note |
|---|
| Subscription Journals | Only open access papers (by design) |
| Real-time Updates | arXiv has ~1-2 day delay |
| Paywalled Content | Cannot access IEEE, ACM, etc. journals |
| Daily Limits | 10,000 requests/day free (email for more) |
| Proprietary Data | Only academic papers, not internal docs |
🔧 Troubleshooting
Problem: Paper Not Found
deepxiv paper invalid_id
Solution:
Problem: Daily Limit Exceeded
deepxiv search "topic"
Solution:
- Wait until tomorrow (limit resets daily)
- OR email
tommy@chien.io with name, email, phone for higher limit
Problem: Token Invalid
deepxiv paper 2409.05591
Solution:
- Run
deepxiv config --token YOUR_NEW_TOKEN
- Or delete
~/.env to auto-register new token
Problem: Agent Dependencies Missing
deepxiv agent query "analyze"
Solution:
pip install deepxiv-sdk[agent]
Problem: Timeout on Large Papers
deepxiv paper <large_paper_id>
Solution:
- Use
--brief or --head instead of full paper
- Or use
--section to read specific parts
- Increase timeout: Use Python API with
Reader(timeout=180)
📊 Output Format Guide
For Search Results
Format: Show title, arxiv_id, brief context
1. Title of Paper (2409.05591)
- Field: Computer Science / AI
- Citations: 150
- Key idea: Brief 1-line summary of main contribution
For Paper Reading
Always mention what command was used:
From `deepxiv paper 2409.05591 --brief`:
- Title: MemGPT: Towards LLMs as Operating Systems
- TLDR: Introduces hierarchical memory management for extended context
- Key concepts: agent memory, context management, LLM systems
- (~500 tokens)
For Structured Data
Use JSON format when:
- Processing results programmatically
- Building pipelines
- Storing for later analysis
deepxiv search "topic" --format json
⏱️ Token Budget Guide
When planning queries, consider token costs:
Quick Summary: 500 tokens
Metadata (--head): 1-2k tokens
One Section: 1-5k tokens (depends on section)
Full Paper: 10-50k tokens
Search Query: 0.5-1k tokens
Agent Analysis: 5-20k tokens (reasoning depth)
Recommendation: For general use, stick to --brief and --section to keep tokens under 5k per query.
🚀 Advanced Usage
Batch Processing (Multiple Papers)
for id in 2409.05591 2504.21776 2503.04975; do
echo "=== $id ==="
deepxiv paper $id --brief
done
Piping to Other Tools
deepxiv search "topic" --format json | jq '.results[] | .arxiv_id'
Custom Token Configuration
from deepxiv_sdk import Reader
reader = Reader(token="YOUR_TOKEN", timeout=120, max_retries=5)
🌐 Supported & Coming Soon
Current Support ✅
- arXiv - Computer Science, Physics, Math, Economics
- PMC - PubMed Central biomedical literature
Coming Soon 🔄
- bioRxiv - Biology preprints
- medRxiv - Medicine preprints
- Other OA - Additional open access sources
- Full OA Ecosystem - Unified cross-source search
📞 Getting Help
Command not working?
deepxiv <command> --help
Need a higher daily limit?
Email: tommy@chien.io with name, email, phone
Found a bug?
GitHub Issues
Learn more?
Full Documentation
✨ Tips & Best Practices
- Start with
--brief - Always start with brief overview
- Use sections - Don't load full papers when sections suffice
- Save tokens - Stack operations to reduce API calls
- Check limits - Run
deepxiv token before large batches
- Use agent wisely - For complex analysis that needs reasoning
- Format choice - Use
--format json for piping, plain text for humans
- Error handling - Always handle "Paper not found" and "Limit exceeded" cases
Last Updated: 2024 | Version: 0.2.0 | Status: Production Ready