nlp-supply-chain
When the user wants to apply NLP to supply chain, extract information from documents, analyze supplier communications, classify items, or process unstructured text. Also use when the user mentions "natural language processing," "NLP," "text mining," "document extraction," "supplier sentiment analysis," "product classification from text," "BERT," "transformers for text," or "chatbots for supply chain." For general ML, see ml-supply-chain.
npx skills add majiayu000/claude-skill-registry --skill nlp-supply-chain-kishorkukreja-awesome-supply-chain --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Natural Language Processing for Supply Chain You are an expert in applying NLP to supply chain problems. Your goal is to extract insights from unstructured text, automate document processing, analyze supplier communications, and classify products using modern NLP techniques. ## Applications 1. **Document Processing**: Purchase orders, invoices, contracts 2. **Product Classification**: Categorize items from descriptions 3. **Supplier Risk Analysis**: Analyze news, reports, sentiment 4. **Demand Sensing**: Social media, reviews, trends 5. **Chatbots**: Customer service, internal queries --- ## Product Classification with BERT ```python from transformers import BertTokenizer, BertForSequenceClassification import torch class ProductClassifier: """ Classify products from text descriptions using BERT """ def __init__(self, num_classes): self.tokenizer = BertTokenizer.from_pretrained('bert-base-uncased') self.model = BertForSequenceClassification.from_pretrained( 'bert-base-uncased', num_labels=num_classes ) def classify(self, product_description): """Classify product from description""" # Tokenize inputs = self.tokenizer( product_description, return_tensors='pt', truncation=True, paddi
- Applications
- Product Classification with BERT
- Named Entity Recognition (NER) for Invoices
- Supplier Risk Sentiment Analysis
- Chatbot for Supply Chain Queries
- Tools & Libraries
- Related Skills
What does the nlp-supply-chain skill do?
When the user wants to apply NLP to supply chain, extract information from documents, analyze supplier communications, classify items, or process unstructured text. Also use when the user mentions "natural language processing," "NLP," "text mining," "document extraction," "supplier sentiment analysis," "product classification from text," "BERT," "transformers for text," or "chatbots for supply chain." For general ML, see ml-supply-chain.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill nlp-supply-chain-kishorkukreja-awesome-supply-chain --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.