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Best Claude skills for AI engineering

AI engineering skills help you build with models: prompt design, evals, fine-tuning, RAG, agent architecture and skill authoring itself. Hugging Face, Google and Orchestra Research publish large packs, and meta-skills help you write better skills.

606 ai engineering skills · ranked live · November 2026

The top 10. Ranked by the Alyn Score.

  1. Anthropic

    Skills

    #1
    Anthropic

    MCP Builder

    Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to…

    Pack192k3.8MScore 93
    Details
  2. Anthropic

    Skills

    #2
    Anthropic

    Skill Creator

    Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to…

    Pack192k3.8MScore 93
    Details
  3. #3
    Matt Pocock

    Domain Modeling

    Build and sharpen a project's domain model. Use when discussing codebase terminology, writing or editing a GLOSSARY.md, or recording or editing an ADR.

    Pack321k33MScore 92
    Details
  4. Jesse Vincent

    Superpowers

    #4
    Jesse Vincent

    Subagent Driven Development

    Use when executing implementation plans with independent tasks in the current session

    Pack316k3.9MScore 92
    Details
  5. Anthropic

    Skills

    #5
    Anthropic

    Claude API

    Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the…

    Pack192k3.8MScore 91
    Details
  6. #6
    affaan-m

    Agent Architecture Audit

    Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering…

    Pack301k1.7MScore 89
    Details
  7. #7
    affaan-m

    Agentic Os

    Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management…

    Pack301k1.7MScore 89
    Details
  8. #8
    affaan-m

    AI Regression Testing

    Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where…

    Pack301k1.7MScore 89
    Details
  9. #9
    JuliusBrussee

    Caveman Setup

    Wire a repository through the Caveman Cloud gateway so every LLM request is measured, with no behavior change. Use for "set up caveman" or adding LLM spend observability.

    Pack119k4.8MScore 88
    Details
  10. Corey Haines

    Marketingskills

    #10
    Corey Haines

    Marketing Psychology

    When the user wants to apply psychology to marketing, or asks why buyers behave or value things as they do, or whether a persuasion tactic is honest: biases, mental models, anchoring…

    Pack60k6.3MScore 86
    Details

What makes a great ai engineering skill.

  • Eval steps so changes are measured, not vibed.

  • Current library versions and APIs.

  • Cost and context awareness for long-running agents.

All 606 ai engineering skills.

OpenAI

Skills

77
OpenAI

security-threat-model

Repository-grounded threat modeling that enumerates trust boundaries, assets, attacker capabilities, abuse paths, and mitigations, and writes a concise Markdown threat model. Trigger only…

Pack29k225kSecurity

Anthropic

Claude Plugins Official

77
Anthropic

session-report

Generate an explorable HTML report of Claude Code session usage (tokens, cache, subagents, skills, expensive prompts) from ~/.claude/projects transcripts.

Pack47k184kCoding
76
thedotmack

claude-mem-install

Use this when setting up claude-mem on Grok Bot: local worker plus CMEM Pro observer (default), optional host-login observer, or remote cmem.ai. No Cursor required.

Pack116k109kProductivity
76
thedotmack

how-it-works

Explain how claude-mem captures observations, when memory injection kicks in, and where data lives. Use when the user asks "how does claude-mem work?" or "what is this thing doing?".

Pack116k109kProductivity
75
Microsoft

airunway-aks-setup

Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: "setup AI Runway"…

Pack1.6k17MAI engineering
75
Microsoft

azure-aigateway

Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate…

Pack1.6k17MDevOps
75
thedotmack

build-and-release

Fully automate building and releasing a coding task.

Pack116k109kDevOps
75
thedotmack

do

Pack116k109kProductivity
75
thedotmack

host-observer

Use this when fulfilling claude-mem observer jobs on Grok Bot: reply only skip_summary or one full observation XML, never prose.

Pack116k109kProductivity

NVIDIA

Skills

75
NVIDIA

kermt-finetune

Finetune a pretrained KERMT encoder on a labeled CSV. Validate the checkpoint and data, prepare features, and run containerized training. Use a local checkpoint or optionally download a…

Pack3.9k429kAI engineering
75
thedotmack

learn-codebase

Prime a codebase by reading every source file in full. Use when starting work on a new or unfamiliar project, or when the user asks to "learn the codebase", "read the codebase", "prime", or…

Pack116k109kCoding
75
thedotmack

make-plan

../../../plugin/skills/make-plan/SKILL.md

Pack116k109kProductivity
75
thedotmack

mem-search

Use this when the user asks to search memory, "did we already solve this?", "how did we do X last time?", or wants work from previous sessions.

Pack116k109kProductivity

Hugging Face

Skills

74
Hugging Face

huggingface-community-evals

Run evaluations for Hugging Face Hub models using inspect-ai and lighteval on local hardware. Use for backend selection, local GPU evals, and choosing between vLLM / Transformers /…

Pack11k42kAI engineering

Hugging Face

Skills

74
Hugging Face

huggingface-llm-trainer

Train or fine-tune language and vision models using TRL (Transformer Reinforcement Learning) or Unsloth with Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling…

Pack11k42kAI engineering

Hugging Face

Skills

74
Hugging Face

huggingface-paper-publisher

Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based…

Pack11k42kAI engineering

Hugging Face

Skills

74
Hugging Face

huggingface-vision-trainer

Trains and fine-tunes vision models for object detection (D-FINE, RT-DETR v2, DETR, YOLOS), image classification (timm models — MobileNetV3, MobileViT, ResNet, ViT/DINOv3 — plus any…

Pack11k42kAI engineering

Hugging Face

Skills

74
Hugging Face

train-sentence-transformers

Train or fine-tune sentence-transformers models across `SentenceTransformer` (bi-encoder, dense or static embedding model for retrieval, similarity, clustering, classification, paraphrase…

Pack11k42kAI engineering

NVIDIA

Skills

73
NVIDIA

codonfm-finetune

Fine-tune public CodonFM Encodon checkpoints on labeled coding-sequence or coding-variant data using LoRA, head-only, or full fine-tuning. Use when a user explicitly asks to fine-tune…

Pack3.9k429kAI engineering
73
davila7

context-window-management

Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot Use when: context window, token limit, context management, context…

Pack33k285kProductivity

Orchestra Research

AI Research SKILLs

73
Orchestra Research

huggingface-accelerate

Simplest distributed training API. 4 lines to add distributed support to any PyTorch script. Unified API for DeepSpeed/FSDP/Megatron/DDP. Automatic device placement, mixed precision…

Pack14k103kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

huggingface-tokenizers

Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies…

Pack14k103kAI engineering

Hugging Face

Skills

73
Hugging Face

huggingface-tool-builder

Use this skill when the user wants to build tool/scripts or achieve a task where using data from the Hugging Face API would help. This is especially useful when chaining or combining API…

Pack11k42kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

implementing-llms-litgpt

Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistral). Use when need clean model implementations, educational…

Pack14k103kAI engineering

NVIDIA

Skills

73
NVIDIA

kermt-infer

Run predictions with a finetuned KERMT checkpoint on a SMILES-only CSV. The skill validates that the input ckpt has task FFN heads (refuses pretrain ckpts with a redirect to…

Pack3.9k429kAI engineering

NVIDIA

Skills

73
NVIDIA

kermt-pretrain-scratch

Pretrain a fresh KERMT model from scratch on a user-provided corpus. Builds a new vocabulary from the corpus, instantiates the model architecture from defaults, and launches pretrain_ddp.py…

Pack3.9k429kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

mamba-architecture

State-space model with O(n) complexity vs Transformers' O(n²). 5× faster inference, million-token sequences, no KV cache. Selective SSM with hardware-aware design. Mamba-1 (d_state=16) and…

Pack14k103kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

miles-rl-training

Provides guidance for enterprise-grade RL training using miles, a production-ready fork of slime. Use when training large MoE models with FP8/INT4, needing train-inference alignment, or…

Pack14k103kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

nanogpt

Educational GPT implementation in ~300 lines. Reproduces GPT-2 (124M) on OpenWebText. Clean, hackable code for learning transformers. By Andrej Karpathy. Perfect for understanding GPT…

Pack14k103kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

nemo-curator

GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII…

Pack14k103kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

nnsight-remote-interpretability

Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on…

Pack14k103kResearch

Orchestra Research

AI Research SKILLs

73
Orchestra Research

openrlhf-training

High-performance RLHF framework with Ray+vLLM acceleration. Use for PPO, GRPO, RLOO, DPO training of large models (7B-70B+). Built on Ray, vLLM, ZeRO-3. 2× faster than DeepSpeedChat with…

Pack14k103kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

peft-fine-tuning

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters…

Pack14k103kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

pyvene-interventions

Provides guidance for performing causal interventions on PyTorch models using pyvene's declarative intervention framework. Use when conducting causal tracing, activation patching…

Pack14k103kAI engineering

Orchestra Research

AI Research SKILLs

73
Orchestra Research

ray-data

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine…

Pack14k103kResearch

Orchestra Research

AI Research SKILLs

73
Orchestra Research

rwkv-architecture

RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at…

Pack14k103kAI engineering

AI engineering skills, explained.

Also searched as: llm skills, prompt engineering skill, fine-tuning skills, skill creator, hugging face skills.

What are the best Claude skills for AI engineering?

Right now the top-ranked ai engineering skills on Alyn are MCP Builder (Anthropic), Skill Creator (Anthropic), Domain Modeling (Matt Pocock). Rankings combine GitHub stars, installs, freshness and depth, and update live.

How do I create my own skill?

Write a folder with a SKILL.md file: YAML frontmatter with name and description, then instructions. See Alyn's guide on creating skills.

Do self-written skills help?

The SkillsBench study found curated skills raised pass rates by 16.2 points on average, while skills the model wrote for itself gave no benefit on average. Quality matters.

How do I install a ai engineering skill?

Run npx skills add owner/repo in your project, or copy the folder with SKILL.md into ~/.claude/skills. Every skill on this page has a ready-to-copy command.

Built a ai engineering skill? Get it ranked.

Submit a skill