Claude skills and agent skills

Clay-HHKSkill

huggingface-tokenizers

Clay-HHK/claude-skills/huggingface-tokenizers/SKILL.md

Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.

Clay-HHKSkill

humanizer

Clay-HHK/claude-skills/humanizer/SKILL.md

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Clay-HHKSkill

instructor

Clay-HHK/claude-skills/instructor/SKILL.md

Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

Clay-HHKSkill

internal-comms

Clay-HHK/claude-skills/internal-comms/SKILL.md

A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communications (status reports, leadership updates, 3P updates, company newsletters, FAQs, incident reports, project updates, etc.).

Often used withskill-share·academy-guide·slack-gif-creator

Clay-HHKSkill

kaggle-learner

Clay-HHK/claude-skills/kaggle-learner/SKILL.md

This skill should be used when the user asks to "learn from Kaggle", "study Kaggle solutions", "analyze Kaggle competitions", or mentions Kaggle competition URLs. Provides access to extracted knowledge from winning Kaggle solutions across NLP, CV, time series, tabular, and multimodal domains.

Clay-HHKSkill

knowledge-distillation

Clay-HHK/claude-skills/knowledge-distillation/SKILL.md

Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. Covers temperature scaling, soft targets, reverse KLD, logit distillation, and MiniLLM training strategies.

Clay-HHKReads credentialsSkill

lambda-labs-gpu-cloud

Clay-HHK/claude-skills/lambda-labs/SKILL.md

Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.

Clay-HHKReads credentialsSkill

langchain

Clay-HHK/claude-skills/langchain/SKILL.md

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.

Clay-HHKReads credentialsSkill

langsmith-observability

Clay-HHK/claude-skills/langsmith/SKILL.md

LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.

Clay-HHKDeletes or force-pushesSkill

latex-conference-template-organizer

Clay-HHK/claude-skills/latex-conference-template-organizer/SKILL.md

Organize messy conference LaTeX template .zip files into clean Overleaf-ready structure. Use when the user asks to "organize LaTeX template", "clean up .zip template", or "prepare Overleaf submission template".

Clay-HHKSkill

implementing-llms-litgpt

Clay-HHK/claude-skills/litgpt/SKILL.md

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 understanding of architectures, or production fine-tuning with LoRA/QLoRA. Single-file implementations, no abstraction layers.

Clay-HHKSkill

llama-cpp

Clay-HHK/claude-skills/llama-cpp/SKILL.md

Runs LLM inference on CPU, Apple Silicon, and consumer GPUs without NVIDIA hardware. Use for edge deployment, M1/M2/M3 Macs, AMD/Intel GPUs, or when CUDA is unavailable. Supports GGUF quantization (1.5-8 bit) for reduced memory and 4-10× speedup vs PyTorch on CPU.

Clay-HHKSkill

llama-factory

Clay-HHK/claude-skills/llama-factory/SKILL.md

Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal support

Clay-HHKSkill

llamaguard

Clay-HHK/claude-skills/llamaguard/SKILL.md

Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.

Clay-HHKSkill

llamaindex

Clay-HHK/claude-skills/llamaindex/SKILL.md

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.

Clay-HHKSkill

llava

Clay-HHK/claude-skills/llava/SKILL.md

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.

Clay-HHKSkill

evaluating-llms-harness

Clay-HHK/claude-skills/lm-evaluation-harness/SKILL.md

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

Clay-HHKSkill

long-context

Clay-HHK/claude-skills/long-context/SKILL.md

Extend context windows of transformer models using RoPE, YaRN, ALiBi, and position interpolation techniques. Use when processing long documents (32k-128k+ tokens), extending pre-trained models beyond original context limits, or implementing efficient positional encodings. Covers rotary embeddings, attention biases, interpolation methods, and extrapolation strategies for LLMs.

Clay-HHKSkill

mamba-architecture

Clay-HHK/claude-skills/mamba/SKILL.md

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 Mamba-2 (d_state=128, multi-head). Models 130M-2.8B on HuggingFace.

Clay-HHKSkill

mcp-builder

Clay-HHK/claude-skills/mcp-builder/SKILL.md

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 integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

Often used withchinese-code-review·codebase-migrate·Problem-Solving Techniques