Data analysis, machine learning, LLM apps, and prompt design (9K skills)
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered performance.
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GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics), semantic deduplication, PII redaction, NSFW detection. Scales across GPUs with RAPIDS. Use for preparing high-quality training datasets, cleaning web data, or deduplicating large corpora.
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Songwriting craft, AI music generation prompts (Suno focus), parody/adaptation techniques, phonetic tricks, and lessons learned. These are tools and ideas, not rules. Break any of them when the art calls for it.
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Optimizes LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.
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Provides PyTorch-native distributed LLM pretraining using torchtitan with 4D parallelism (FSDP2, TP, PP, CP). Use when pretraining Llama 3.1, DeepSeek V3, or custom models at scale from 8 to 512+ GPUs with Float8, torch.compile, and distributed checkpointing.
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Generate ASCII art using pyfiglet (571 fonts), cowsay, boxes, toilet, image-to-ascii, remote APIs (asciified, ascii.co.uk), and LLM fallback. No API keys required.
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Query Solana blockchain data with USD pricing — wallet balances, token portfolios with values, transaction details, NFTs, whale detection, and live network stats. Uses Solana RPC + CoinGecko. No API key required.
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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
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Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.
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Query Base (Ethereum L2) blockchain data with USD pricing — wallet balances, token info, transaction details, gas analysis, contract inspection, whale detection, and live network stats. Uses Base RPC + CoinGecko. No API key required.
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Search context data(memories, skills and resource) from OpenViking Context Database (aka. ov). Trigger this tool when 1. need information that might be stored as memories, skills or resources on OpenViking; 2. is explicitly requested searching files or knowledge; 3. sees `search context`, `search openviking`, `search ov` request.
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This skill adds data(like resources) to OpenViking Context Database (aka. ov). Use when an agent needs to add files, data from URLs, or external knowledge during interactions. Trigger this tool when 1. is explicitly requested adding files or knowledge; 2. identifies valuable resources worth importing; 3. the user mentioned adding to OV/OpenViking/Context Database. This skill helps how to use CLI like `ov add-resource`, `ov add-skill` and `ov add-memory` to add resource data, skill files, memory files to OpenViking.
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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
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Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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Bloomberg-style financial trading terminal: dark-only, data-dense, cyan/coral buy-sell signals, monospace tabular data. Everything readable at a glance from two meters.
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Fighter-jet / helicopter head-up display: phosphor green on near-black, all-caps data overlays, angular geometry. Zero ambiguity at speed and altitude. For flight-sim UIs, telemetry, and command-and-control displays.
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Clean, high-contrast enterprise design for data-driven workflows with intuitive drag-and-drop patterns and structured layouts.
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数据驱动的小红书 / 公众号社交卡 — 一个 hero 数字 + 解释、KPI 塔（3-5 指标堆叠）、前后对比、横向迷你条形图、排行榜带高亮行、ROI 卡。必须标单位 / 时间窗 / 数据来源，必须一个数字视觉主导。触发："做个 KPI 卡 / 数据卡 / 排行榜卡 / 增长卡 / 复盘数字卡"。NOT 表情绪 / 引言 / 图主导的卡，NOT chartjunk。
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Structured, enterprise-focused design system emphasizing clarity, consistency, and efficiency for data-dense web applications.
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Query PostgreSQL with pg and navigate Openrind Shell's primary FUSE or compatibility workspace; /db is custom-agent-only.
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Develop Openrind Shell's OpenShell-supervised PostgreSQL FUSE runtime, compatibility sync runtime, and just-bash library.
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Launch and diagnose the required Haloop-routed PostgreSQL FUSE runtime in Openrind Desktop.
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Constrói prompts para geradores de imagem e vídeo — estrutura, parâmetros, referência de estilo e negativa. Use quando o usuário disser "prompt", "como pedir isso pra IA", "melhorar o prompt", "não saiu como eu queria", "prompt do Ideogram", "prompt do Flux", ou antes de qualquer chamada de geração. Competência central deste plugin — a qualidade do prompt define o custo da campanha.
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Mantém coerência visual entre peças geradas por IA — seed, modelo fixo, referência de estilo e biblioteca de prompts da marca. Use quando o usuário disser "as peças não parecem da mesma campanha", "manter o estilo", "consistência", "cada imagem saiu diferente", "padronizar o visual gerado". É o problema mais difícil de geração por IA em escala.
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