AI Infrastructure Agent Skills

# AI Infrastructure Agent Skills

> **⚠️ WARNING**
> This project is under active development and heavily generated by LLMs without strict proofreading. Use with caution and verify all code before production use.

A collection of specialized agent skills for AI infrastructure development, enabling Claude Code to write, optimize, and debug high-performance systems.

## Overview

This repository provides expert-level skills for AI infrastructure engineering tasks. Each skill packages domain knowledge, code examples, and best practices to transform Claude into a specialized developer for specific frameworks and tools.

### Construction Methodology (Unless Otherwise Specified)

1. **Knowledge Gathering**: Use Gemini DeepResearch to collect comprehensive, up-to-date information on target frameworks
2. **Skill Development**: Transform research into structured skills using `skill-creator` in Claude Code
3. **Validation**: Test skill-generated code examples to ensure correctness
4. **Maintenance**: Regular updates based on latest official documentation

## Available Skills

### TileLang Developer
Write high-performance GPU kernels using TileLang for NVIDIA, AMD, and Ascend hardware.

**Capabilities:**
- Matrix multiplication (GEMM) kernels
- FlashAttention implementations
- DeepSeek MLA operators
- Performance optimization (swizzle layouts, pipelining, warp specialization)
- Cross-platform kernel development

**Status:** ✅ Complete

### Megatron Memory Estimator
Estimate GPU memory usage for Megatron-based MoE and dense models. Built upon [megatron_memory_estimator](https://huggingface.co/spaces/ISEEKYAN/megatron_memory_estimator).

**Capabilities:**
- Estimate memory from HuggingFace configs
- Support for MoE models (DeepSeek-V3, Qwen, etc.)
- Parallelism strategy comparison (TP/PP/EP/CP)
- Memory optimization recommendations

**Status:** ✅ Complete

### SLIME User
Guide for using SLIME (LLM post-training framework for RL Scaling). Built upon [THUDM/slime](https://github.com/THUDM/slime).

**Capabilities:**
- RL training setup and configuration (GRPO, GSPO, PPO, Reinforce++)
- Multi-turn tool calling and agent workflows
- Custom reward models and generation functions
- Megatron and FSDP backend configuration
- SGLang integration and optimization
- Dynamic sampling and partial rollout
- Multi-node distributed training

**Status:** ✅ Complete

Prompt to create this skill, with Sonnet 4.5:

```
Use skill-creator to create a skill called slime-user at this repo. slime is an LLM
post-training framework for RL Scaling. Its repo is https://github.com/THUDM/slime.

Skill creation procedure:

1. Git clone the latest repo
2. Analyze `docs/en`, understand basic structure and write a doc navigation guide for user
getting started or finding docs for advanced usage
3. Gather valuable examples from the docs and `examples` dir, write key ideas and script
path down for quick reference
4. Checkout some important source code, for example `slime/slime/utils/arguments.py` and
`slime/rollout/sglang_rollout.py`, provide its path and functions for a quick find.
```

### TikZ Flowchart
Create professional flowcharts and architecture diagrams using LaTeX TikZ with standardized styles.

**Capabilities:**
- Professional flowcharts with Google Material-like color palette
- Standardized node types (data, memory, operation, kernel boxes)
- Architecture diagrams and process flows
- Grouping and layout best practices
- Clean orthogonal edges and relative positioning

**Status:** ✅ Complete

## Planned Skills

### SGLang Developer
Development skill for SGLang (Structured Generation Language) runtime and optimization.

**Planned capabilities:**
- SGLang runtime configuration
- Custom sampling strategies
- Performance tuning for LLM inference
- Multi-GPU serving optimization

**Status:** 🚧 Planned

### vLLM Developer
Skill for vLLM engine development and deployment.

**Planned capabilities:**
- PagedAttention implementation
- Custom scheduler development
- Multi-LoRA serving
- Quantization integration

**Status:** 🚧 Planned

## Usage

### Installing Skills

Skills are installed by placing the skill directory in Claude's skills path:

**Natural Language:**
Ask Claude Code directly: "Help me install skills from https://github.com/yzlnew/infra-skills"

**Personal (across all projects):**
```bash
# Clone and copy to personal skills directory
git clone https://github.com/yzlnew/infra-skills.git
mkdir -p ~/.claude/skills
cp -r infra-skills/tilelang-developer ~/.claude/skills/
cp -r infra-skills/megatron-memory-estimator ~/.claude/skills/
cp -r infra-skills/slime-user ~/.claude/skills/
cp -r infra-skills/tikz-flowchart ~/.claude/skills/
```

**Project-level (for repository collaborators):**
```bash
# Clone and copy to project's skills directory
cd your-project
git clone https://github.com/yzlnew/infra-skills.git .claude/skills-repo
mkdir -p .claude/skills
cp -r .claude/skills-repo/tilelang-developer .claude/skills/
cp -r .claude/skills-repo/megatron-memo

... (truncated)