npcpy-research-guide

npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill npcpy-research-guide --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# npcpy Research Guide ## Overview npcpy is an all-in-one Python library that combines NLP, agent orchestration, and knowledge graph capabilities in a single package. It provides tools for text processing, entity extraction, agent creation, graph-based reasoning, and research automation. Designed as a Swiss Army knife for AI researchers who need quick access to diverse NLP and agent capabilities without juggling many dependencies. ## Installation ```bash pip install npcpy ``` ## Core Modules ### NLP Processing ```python from npcpy import NLP nlp = NLP() # Text processing pipeline doc = nlp.process( "Transformers have revolutionized NLP since Vaswani et al. " "introduced the attention mechanism in 2017." ) # Named entities for entity in doc.entities: print(f"[{entity.type}] {entity.text}") # [METHOD] Transformers # [PERSON] Vaswani # [CONCEPT] attention mechanism # [DATE] 2017 # Key phrases print(doc.key_phrases) # ["attention mechanism", "Transformers", "NLP"] # Sentiment / stance print(doc.sentiment) # positive ``` ### Agent Creation ```python from npcpy import Agent, Tool # Create a research agent agent = Agent( name="research_assistant", llm_provider="anthropic", tools=[ Tool("w

pip install npcpy