swift-mlx-lm
MLX Swift LM - Run LLMs and VLMs on Apple Silicon using MLX. Covers local inference, streaming, wired memory coordination, tool calling, LoRA fine-tuning, embeddings, and model porting.
algorand-ecosystem
Catalog of major projects, protocols, and tools in the Algorand ecosystem. Use when the user asks about Algorand ecosystem projects, DeFi protocols (Folks Finance, Tinyman, Pact, Haystack, Vestige, AlphaArcade), wallets (Pera, Lute, Defly), bridges and cross-chain swaps (XO Swap, SimpleSwap, Allbridge, Wormhole NTT), blockchain explorers and dashboards (Allo, Algo Surf, Lora, Pera Explorer, Nodely, DeFi Llama), NFT marketplaces and tools (Downbad, Rand Gallery, Wen Tools, Minthol, NFDomains, GoPlausible), impact projects (AID Tech, HesabPay, Wholechain), or real world assets / RWA (Meld Gold, Lofty). Also use when the user wants to find relevant integrations, community projects, SDKs, or APIs available in the Algorand ecosystem.
training-hub-guide
Guides users through LLM post-training with Training Hub, including installation, algorithm selection (SFT, OSFT, LoRA), hyperparameter tuning, troubleshooting OOM errors, interpreting loss curves, and leveraging backend-specific features. Use when the user is working with training_hub, fine-tuning language models, asking about SFT/OSFT/LoRA training, or debugging GPU/CUDA training issues.
book-sft-pipeline
This skill should be used when the user asks to "fine-tune on books", "create SFT dataset", "train style model", "extract ePub text", or mentions style transfer, LoRA training, book segmentation, or author voice replication.