Skillzwave Logo
Skillzwave

mastering-pytorch-rl-nlp

93
A

Expert guidance for PyTorch development covering Deep Reinforcement Learning and NLP Transformers.This skill provides comprehensive knowledge for building RL agents with TorchRL (DQN, PPO) andNLP systems with HuggingFace Transformers. Use this skill when working with PyTorch 2.7+,implementing reinforcement learning algorithms, fine-tuning transformer models, or deployingML systems to production. Includes current best practices, verified library versions (Dec 2025),and warnings about depr...

#Reinforcement Learning#Deep Reinforcement#NLP#Quick Start#Transformers#Apple Silicon#Learning#HuggingFace Transformers

Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security

Installation for Agentic Skill

View all platforms →
skilz install SpillwaveSolutions/mastering-pytorch-rl-nlp-agentic-skill/mastering-pytorch-rl-nlp
skilz install SpillwaveSolutions/mastering-pytorch-rl-nlp-agentic-skill/mastering-pytorch-rl-nlp --agent opencode
skilz install SpillwaveSolutions/mastering-pytorch-rl-nlp-agentic-skill/mastering-pytorch-rl-nlp --agent codex
skilz install SpillwaveSolutions/mastering-pytorch-rl-nlp-agentic-skill/mastering-pytorch-rl-nlp --agent gemini

First time? Install Skilz: pip install skilz

Works with 22+ AI coding assistants

Cursor, Aider, Copilot, Windsurf, Qwen, Kimi, and more...

View All Agents
Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/SpillwaveSolutions/mastering-pytorch-rl-nlp-agentic-skill
2. Copy the agent skill directory:
cp -r mastering-pytorch-rl-nlp-agentic-skill ~/.claude/skills/
View on GitHub

Need detailed installation help? Check our platform-specific guides:

Claude Desktop Guide Claude Code Guide Troubleshooting

Related Agentic Skills

automating-mail

by SpillwaveSolutions

Automates Apple Mail via JXA with AppleScript dictionary discovery. Use when asked to "automate email", "send mail via script", "JXA Mail automatio...

100
Marketplace

automating-reminders

by SpillwaveSolutions

Automates Apple Reminders using JavaScript for Automation (JXA). Use when asked to "create reminders programmatically", "automate reminder lists", ...

100
Marketplace

mastering-postgresql

by SpillwaveSolutions

PostgreSQL development for Python with full-text search (tsvector, tsquery, BM25 via pg_search), vector similarity (pgvector with HNSW/IVFFlat), JS...

100
Marketplace

automating-contacts

by SpillwaveSolutions

Automates macOS Contacts via JXA with AppleScript dictionary discovery. Use when asked to "automate contacts", "JXA contacts automation", "macOS ad...

99
Marketplace

Agentic Skill Details

Owner
SpillwaveSolutions (GitHub)
Repository
mastering-pytorch-rl-nlp-agentic-skill
Type
Other
Meta-Domain
Primary Domain
Market Score
93
Agentic Skill Grades →

Agent Skill Grade

A
Score: 93/100 Click to see breakdown

Score Breakdown

Spec Compliance
12/15
PDA Architecture
27/30
Ease of Use
22/25
Writing Style
9/10
Utility
18/20
Modifiers: +5

Areas to Improve

  • Description needs trigger phrases
  • Missing TOC in reference files
  • No explicit numbered workflows

Recommendations

  • Add trigger phrases to description for discoverability
  • Add table of contents for files over 100 lines

Graded: 2026-01-19

Developer Feedback

I took a look at your mastering-pytorch-rl-nlp skill and wanted to share some thoughts.

Links:

The TL;DR

You're at 93/100, solid A-grade territory. This is based on Anthropic's skill best practices. Your strongest area is Progressive Disclosure Architecture (27/30) — the reference structure is genuinely well-organized. Weakest is Spec Compliance (12/15), which is an easy fix that'll get you to 95+.

What's Working Well

  • Reference architecture is chef's kiss — Five separate guides (fundamentals, RL, NLP, optimization, advanced) are perfectly one level deep from SKILL.md. The separation between quick-start and deep-dive is exactly right.
  • Trigger coverage is comprehensive — You've got 25+ specific triggers (pytorch, torchrl, gymnasium, huggingface, BERT, GPT, DQN, PPO, LoRA). That's serious discoverability.
  • Version accuracy and deprecation warnings — The inline notes about deprecated APIs (e.g., eval_strategy vs old evaluation_strategy) and PyTorch 2.0+ breaking changes are genuinely helpful and prevent user headaches.
  • Concrete code examples throughout — Input/output pairs for training loops, device handling, and model loading. No fluff, just working code.

The Big One: Missing Trigger Phrases in Description

Your description field is missing the trigger phrase pattern. Right now it says:

description: Expert guidance for PyTorch development covering Deep Reinforcement Learning and NLP Transformers.

It needs to include trigger phrases so Claude and other agents know when to invoke you:

description: Expert guidance for PyTorch development covering Deep Reinforcement Learning and NLP Transformers. Use when asked to "build a PyTo...

AI-Detected Topics

Extracted using NLP analysis

Reinforcement Learning Deep Reinforcement NLP Quick Start Transformers Apple Silicon Learning HuggingFace Transformers transformer models PyTorch

Report Security Issue

Found a security vulnerability in this agent skill?