Use when designing or reviewing AI/ML integration code — covers RAG pipeline design, prompt engineering, structured output with schema validation, tool use/function calling, LLM error handling, token budget management, hallucination mitigation, and AI/ML anti-patterns with examples in TypeScript and Python.
Build AI agents with structured access to Sanity content via Sanity Context. Use when setting up a Sanity-powered chatbot, connecting an AI assistant to Sanity content, or adding client-side tools to an agent. Covers Studio setup, agent implementation, and advanced patterns. Always use this skill when users mention…
★not rated 6▲
+2 todayA✓ AI reviewSocket: passSnyk: warn127 tokens
An AI health-analysis system that combines different kinds of health data, finds unusual patterns, estimates health risks, and generates personalised advice and reports.
Use for on-device or server inference that is not tied to one vendor model: ONNX Runtime, Sentis, Barracuda legacy, custom .onnx/.tflite/.pb assets, and swapping models without rewriting gameplay code.
Local hybrid retrieval (BM25 + ChromaDB vector + BGE-Reranker) over /.deep-memory hot and cold stores. Use when high-accuracy code/solution retrieval is needed and hallucination must be minimized. Typically invoked by deep-memory.
Use Chutes.ai from Hermes for model discovery, routing, account/API-key guidance, and OpenAI-compatible inference. Prefer the live models endpoint for current availability and capabilities.
Reference Claude Code's prompt engineering patterns for AI/Agent development. Provides best practices for system prompts, tool design, agent orchestration, and safety.
Discover and assemble a task-specific prompt from the embedded PromptKit catalog through the PromptKitty CLI. Use when the user wants to select a PromptKit template, compose a prompt for an engineering task, run an interactive PromptKit intake, write a requirements or design artifact, investigate a bug, review code…
Author, validate, consume, and navigate Open Knowledge Format (OKF) knowledge bundles — directories of markdown files with YAML frontmatter that describe datasets, tables, metrics, APIs, playbooks, and attested computations. Use this skill whenever the user mentions OKF, knowledge bundles, a knowledge catalog…
Process large volumes of requests using Gemini Batch API via scripts/. Use for batch processing, bulk text generation, processing JSONL files, async job execution, and cost-efficient high-volume AI tasks. Triggers on "batch processing", "bulk requests", "JSONL", "async job", "batch job".
Use when designing, reviewing, generating, or refactoring React applications built with Effector, effector-react, Farfetched, Atomic Router, @effector/next, patronum, effector-storage, forms, i18n, testing, and related Effector ecosystem tooling. For Feature-Sliced Design project structure and placement decisions, use…
Plan, explain, build, run, monitor, validate, transfer, and audit reproducible embodied-model studies and batch episode collection. Use when a user wants to connect a local, SSH, or cloud GPU host; understand and compare a policy, VLA, world model, world-action model, or hybrid with a benchmark; discover and reuse…
Guides and validates architecture-aware ports of PyTorch/Hugging Face models to Apple MLX, inspects existing local MLX projects, and plans evidence-gated optimizations for Apple Silicon. Use when the user asks to run, port, convert, inspect, quantize, benchmark, or fix a model (LLM, VLM, audio/TTS/ASR, diffusion, SSM…
A comprehensive toolkit for interacting with Kaggle competitions: uploading notebooks, submitting predictions, downloading data, checking status, and viewing leaderboards.
Submit a training job to the Databricks GPU cluster, wait for results, and pull MLflow metrics back locally. Use when the user wants to train on GPU, run a full experiment, or execute code on the Databricks cluster. Triggers on "run on Databricks", "train on GPU", "submit job", "full training run".
Set up and manage a fully local multimodal knowledge base using Gemini Embedding 2 and ChromaDB. Use when user wants to create a business knowledge base, ingest videos/images/audio/docs for RAG, query their knowledge base, or set up multimodal embeddings for their Claude Code agent.
A machine-learning guide to causal inference, which estimates whether one factor causes a change in another. It covers DML, causal forests, DoWhy, and AIPW methods.
Backend architecture, API design, and ML/AI systems expertise. Use for API design, data flows, ML pipelines, embeddings, vector databases, or architectural decisions. Researches best practices via Perplexity when uncertain.
Build the Snowmart real-time log analytics pipeline for the Snowpipe Streaming + Dynamic Tables VHOL. Loads the exact object model, naming, and DDL patterns so short prompts produce consistent objects. Use when: building the streaming pipeline, Bronze/Silver/Gold, semantic view, SRE agent, or dashboard for this lab.…
Discover, install, and run reusable AI prompt skills from the BetterPrompt registry via the CLI (betterprompt / bp). Use when a user needs to find a prompt skill, generate AI output (text, images, video), or manage their skill library. Covers installation, auth, skill discovery, generation, and output review for…
Search, compare, and analyze LLM model benchmarks using data from Artificial Analysis (artificialanalysis.ai). Use this skill whenever the user asks about model selection, model comparison, benchmark scores, pricing, speed, or wants to know which model is best for a task. Also use when the user mentions "Artificial…
YOLO detection, segmentation, classification, and pose estimation setup, training workflow, evaluation metrics, and XAI verification.
★not rated 5 3mo agoA28 tokens
originalMIT
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: