stripe-checkout
Stripe Checkout integration for programme purchases with Server Actions, webhook signature verification, and success/cancel flows. Use when implementing payments, creating checkout sessions, handling webhooks, or setting up purchase flows.
sitemap-robots
Automated sitemap generation for all locale URLs, robots.txt configuration, and llms.txt for AI crawler optimization. Use when setting up sitemap.xml, configuring crawling rules, or improving discoverability for search engines and AI systems.
email-resend
Email sending via Resend API for contact forms and booking requests with locale-aware templates. Use when implementing email notifications, contact form submissions, or transactional emails.
responsive-mobile-first
Mobile-first responsive patterns with sticky headers, floating CTAs, accessible navigation, and touch-friendly interactions. Use when implementing responsive layouts, mobile navigation, or ensuring touch-friendly UI.
nextjs-app-router
Next.js 15 App Router patterns for Server/Client Components, async params, layouts, route handlers, Server Actions, and data fetching. Use when creating routes, pages, layouts, API endpoints, or implementing form submissions with revalidation.
next-intl-i18n
next-intl internationalization for 6 locales (pt-PT, en, tr, es, fr, de) with locale-prefixed routing, useTranslations/getTranslations patterns, and message file structure. Use when adding translations, creating localized pages, implementing language switchers, or handling locale routing.
accessibility-a11y
Semantic HTML, keyboard navigation, focus states, ARIA labels, skip links, and WCAG contrast requirements. Use when ensuring accessibility compliance, implementing keyboard navigation, or adding screen reader support.
component-architecture
Reusable component patterns for cards, sections, forms, and layouts with consistent prop interfaces and composition strategies. Use when creating new components, refactoring existing ones, or establishing component design patterns.
repo_facts
Summarize an arbitrary code repo (git or non-git) into a small, high-signal facts packet: languages, build/test tooling clues, notable paths, and size stats.
ctx
Extract a small, high-signal context packet around ripgrep matches (bounded by hits/files/output budget) for fast LLM consumption.
def
Locate symbol definitions quickly (precise for Python via AST; conservative candidates for other languages) and print a bounded context packet.
sym
List Python symbols (classes/functions) quickly via AST to discover real identifiers before using `def`/`ctx`.
Society in Silico Writing Style
Auto-activates when writing or editing prose in the manuscript/ directory. Applies Max Ghenis's direct, active voice, data-driven writing style.
Society in Silico Book Structure
Auto-activates when navigating or organizing the manuscript. Knows the book's structure, chapter organization, and file conventions.
prompt-creator-10-frameworks
Use when the user asks to create prompts/提示词 for a topic and expects 10 variants using ICIO, CRISPE, BROKE, CREATE, TAG, RTF, ROSES, APE, RACE, TRACE, with strict formatted output (字段清单 + “Prompt：”行 + 分隔符) and a “best prompt” pick with reasons.
reducing-entropy
Manual-only skill for minimizing total codebase size. Only activate when explicitly requested by user. Measures success by final code amount, not effort. Bias toward deletion.
whalefall-version-update
WhaleFall(鲸落) 全局版本更新/发版同步工作流. 用于 bump 版本号(语义化 MAJOR.MINOR.PATCH)、消除 APP_VERSION/pyproject/env/uv.lock/部署脚本/健康检查/页脚/错误页/README/CHANGELOG/About 时间轴的版本漂移,并提供自检脚本与提交/PR 模板.
career-advisor
Career Advisor agent for PhD application planning and career management. Helps with university research, application tracking, professor matching, and career documentation.
youtube
Extract subtitles, frames, and metadata from YouTube videos. Use when user shares a YouTube URL and wants transcript, screenshots, or video analysis.
unity-migration
Migrate a browser-based JavaScript/Canvas game to Unity (C#). Use for Shelter 2250 (or similar) when you need: (1) Unity project setup decisions (2D/URP/input/UI), (2) mapping existing JS classes/systems to Unity architecture, (3) porting core simulation loops (time/resources/rooms/dwellers/save), and (4) planning incremental milestones with parity checks.
unity-bootstrap
Bootstrap a new Unity project for a 2D management/simulation game. Use when you need to create the Unity project, choose URP/UI approach, set up folder structure, gitignore, packages (Input System/TextMeshPro), and establish a minimal scene + tick loop scaffold before porting gameplay systems.
morpho-solana-frontend
Build production-ready frontend for Morpho Blue lending protocol on Solana. Covers all 26 program instructions across supply/borrow, flash loans, liquidations, authorization, and admin features. Uses Next.js 14, Anchor client, Jupiter wallet adapter, and Kamino-style UI/UX. Integrates with morpho-solana-builder skill for contract understanding.
unsloth-grpo
Implementation of Group Relative Policy Optimization (GRPO) for training reasoning models, optimized for 8x memory savings (triggers: GRPO, reasoning, DeepSeek-R1, reinforcement learning, RLVR, GRPOTrainer, thinking tokens).
unsloth-long-context
Training models on extended context lengths using optimized RoPE scaling and memory-efficient attention kernels. Triggers: long context, max_seq_length, rope scaling, large context window, flex attention.
unsloth-models
Guidance on selecting and configuring supported model architectures like Llama 4, DeepSeek-R1, and Qwen3. Triggers: llama 4, deepseek-r1, qwen3, gemma 3, model selection, instruct vs base.
unsloth-orpo
One-step preference alignment using Odds Ratio Preference Optimization (ORPO) (triggers: ORPO, preference optimization, alignment, ORPOTrainer, log_odds_ratio, binary preference).
unsloth-qlora
Advanced 4-bit quantization techniques using Unsloth and BitsAndBytes for extreme VRAM efficiency (triggers: QLoRA, 4-bit, load_in_4bit, bnb-4bit, VRAM optimization, dynamic quantization).
unsloth-quantization
Utilizing Dynamic 4-bit quantization, FP8 training, and 8-bit optimizers to minimize VRAM usage without sacrificing accuracy. Triggers: quantization, dynamic 4-bit, fp8, bitsandbytes, adamw_8bit, qat.
unsloth-sft
Supervised fine-tuning using SFTTrainer, instruction formatting, and multi-turn dataset preparation with triggers like sft, instruction tuning, chat templates, sharegpt, alpaca, conversation_extension, and SFTTrainer.
unsloth-stt
Fine-tuning Speech-to-Text models like Whisper using Unsloth's optimized LoRA pipeline. Triggers: stt, whisper, transcription, audio fine-tuning, speech-to-text, audio normalization.
unsloth-tts
Fine-tuning Text-to-Speech (TTS) models with Unsloth for voice cloning and synthetic speech (triggers: TTS, text-to-speech, voice cloning, Orpheus-TTS, audio fine-tuning, speech synthesis).
unsloth-vision
Fine-tuning multimodal vision-language models (Llama 3.2 Vision, Qwen2.5 VL) using optimized vision layers (triggers: vision models, multimodal, Llama 3.2 Vision, Qwen2.5 VL, UnslothVisionDataCollator, finetune_vision_layers).
vector-databases
Design vector database ingestion and retrieval pipelines (points + payloads, filtered similarity search, multi-stage hybrid retrieval, index maintenance). Use when building RAG/vector search flows or debugging retrieval quality; triggers: vector database, RAG, embeddings, hybrid search, filtered search, Qdrant, Weaviate, Chroma.
unsloth-lora
Configuring and optimizing 16-bit Low-Rank Adaptation (LoRA) and Rank-Stabilized LoRA (rsLoRA) for efficient LLM fine-tuning using triggers like lora, qlora, rslora, rank selection, lora_alpha, lora_dropout, and target_modules.
torchserve
Model serving engine for PyTorch. Focuses on MAR packaging, custom handlers for preprocessing/inference, and management of multi-GPU worker scaling. (torchserve, mar-file, handler, basehandler, model-archiver, inference-api)
torchtext
Natural Language Processing utilities for PyTorch (Legacy). Includes tokenizers, vocabulary building, and DataPipe-based dataset handling for text processing pipelines. (torchtext, tokenizer, vocab, datapipe, regextokenizer, nlp-pipeline)
torchvision
Computer vision library for PyTorch featuring pretrained models, advanced image transforms (v2), and utilities for handling complex data types like bounding boxes and masks. (torchvision, transforms, tvtensor, resnet, cutmix, mixup, pretrained models, vision transforms)
unsloth-core
Core fundamentals of Unsloth for fast LLM fine-tuning, covering FastLanguageModel setup, optimized gradient checkpointing, and native inference acceleration (triggers: unsloth, FastLanguageModel, from_pretrained, get_peft_model, for_inference, gradient checkpointing).
unsloth-cpt
Strategies for continued pretraining and domain adaptation in Unsloth (triggers: continued pretraining, CPT, domain adaptation, lm_head, embed_tokens, rsLoRA, embedding_learning_rate).
unsloth-datasets
Standardizing and formatting datasets for Unsloth, including chat template conversion and synthetic data generation (triggers: chat templates, ShareGPT, Alpaca, conversation_extension, add_new_tokens, standardize_sharegpt, formatting_prompts_func).
unsloth-dpo
Direct Preference Optimization (DPO) for aligning models with preference data without separate reward models. Triggers: dpo, preference optimization, rlhf, ref_model=none, patchdpotrainer, dpotrainer.
unsloth-fft
Performing full fine-tuning (FFT) in Unsloth with 100% exact weight updates and optimized gradient checkpointing. Triggers include fft, full fine-tuning, full_finetuning, exact fine-tuning, and weight updates.
unsloth-gguf
Exporting fine-tuned models to GGUF format for deployment in llama.cpp, Ollama, and local serving tools. Triggers: gguf, quantization export, llama.cpp, ollama, save_pretrained_gguf, modelfile.
unsloth-inference
Deploying fine-tuned models for production inference using native kernel optimization, vLLM, or SGLang. Triggers: inference, serving, vllm, sglang, for_inference, model merging, openai api.
notion-meeting-intelligence
Prepare meeting materials with Notion context and Codex research; use when gathering context, drafting agendas/pre-reads, and tailoring materials to attendees.
gh-address-comments
Help address review/issue comments on the open GitHub PR for the current branch using gh CLI; verify gh auth first and prompt the user to authenticate if not logged in.
gh-fix-ci
Inspect GitHub PR checks with gh, pull failing GitHub Actions logs, summarize failure context, then create a fix plan and implement after user approval. Use when a user asks to debug or fix failing PR CI/CD checks on GitHub Actions and wants a plan + code changes; for external checks (e.g., Buildkite), only report the details URL and mark them out of scope.
pytorch-quantization
Techniques for model size reduction and inference acceleration using INT8 quantization, including Post-Training Quantization (PTQ) and Quantization Aware Training (QAT). (quantization, int8, qat, fbgemm, qnnpack, ptq, dequantize)
pytorch-onnx
Exporting PyTorch models to ONNX format for cross-platform deployment. Includes handling dynamic axes, graph optimization in ONNX Runtime, and INT8 model quantization. (onnx, onnxruntime, torch.onnx.export, dynamic_axes, constant-folding, edge-deployment)
agentic-patterns
Design and operate multi-agent orchestration patterns (ReAct loops, evaluator-optimizer, orchestrator-workers, tool routing) for LLM systems. Use when building or debugging agent workflows, tool-use loops, or multi-step task delegation; triggers: agentic, multi-agent, orchestration, ReAct, evaluator-optimizer, tool-use, handoff.
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