Agent skill · AI & Agents

nlp-engineer

Expert in Natural Language Processing, designing systems for text classification, NER, translation, and LLM integration using Hugging Face, spaCy, and LangChain. Use when building NLP pipelines, text analysis, or LLM-powered features. Triggers include "NLP", "text classification", "NER", "named entity", "sentiment analysis", "spaCy", "Hugging Face", "transformers".

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill nlp-engineer-skill-404kidwiz-claude-supercode-ski --agent claude-code

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

Facts
Files in the skill folder: 2
SKILL.md size: 3 KB
Bundled scripts: none
Path: skills/ai-ml/nlp-engineer-skill-404kidwiz-claude-supercode-ski/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# NLP Engineer ## Purpose Provides expertise in Natural Language Processing systems design and implementation. Specializes in text classification, named entity recognition, sentiment analysis, and integrating modern LLMs using frameworks like Hugging Face, spaCy, and LangChain. ## When to Use - Building text classification systems - Implementing named entity recognition (NER) - Creating sentiment analysis pipelines - Fine-tuning transformer models - Designing LLM-powered features - Implementing text preprocessing pipelines - Building search and retrieval systems - Creating text generation applications ## Quick Start **Invoke this skill when:** - Building NLP pipelines (classification, NER, sentiment) - Fine-tuning transformer models - Implementing text preprocessing - Integrating LLMs for text tasks - Designing semantic search systems **Do NOT invoke when:** - RAG architecture design → use `/ai-engineer` - LLM prompt optimization → use `/prompt-engineer` - ML model deployment → use `/mlops-engineer` - General data processing → use `/data-engineer` ## Decision Framework ``` NLP Task Type? ├── Classification │ ├── Simple → Fine-tuned BERT/DistilBERT │ └── Zero-shot → LLM with prompti

What's inside
Steps it walks through
  1. Purpose
  2. When to Use
  3. Quick Start
  4. Decision Framework
  5. Core Workflows
  6. 1. Text Classification Pipeline
  7. 2. NER System
  8. 3. Embedding-Based Search
  9. Best Practices
  10. Anti-Patterns
Ships with 1 file
  • metadata.json
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About this skill
What does the nlp-engineer skill do?

Expert in Natural Language Processing, designing systems for text classification, NER, translation, and LLM integration using Hugging Face, spaCy, and LangChain. Use when building NLP pipelines, text analysis, or LLM-powered features. Triggers include "NLP", "text classification", "NER", "named entity", "sentiment analysis", "spaCy", "Hugging Face", "transformers".

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill nlp-engineer-skill-404kidwiz-claude-supercode-ski --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.

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