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Found 260 Skills
Extract and organize frames from a Bilibili video (bangumi episode, UP upload, or a local file) into scenery shots and per-character image groups, using anime-specific person detection + CCIP character-identity embeddings. Two modes — cluster everyone, or pull out one (or several) named characters via reference folders. Use when the user wants to collect, extract, or organize anime frames/screenshots by character or by scenery from a Bilibili video. Read-only download for personal viewing/analysis; uploads nothing.
Metric-learning recognition (ml-recog) for fine-grained visual recognition. Learns embeddings for retrieval-based matching (e.g., retail product recognition) using triplet / contrastive losses. Use when training, evaluating, exporting, or running inference for a TAO metric-learning recognition model. Trigger phrases include "train metric learning", "ml-recog", "retrieval embeddings", "triplet loss recognition", "fine-grained matching".
Ancient text restoration, attribution, dating, contextualization, and embedding via Aeneas (Latin) / Ithaca (Ancient Greek). Use when asked to "restore", "attribute", "date", "contextualize", "find parallels", "where was it written", "when was it written", "embed", or "analyze" an ancient text, inscription, or epigraphic document, or when the user mentions "Aeneas", or "Ithaca".
Configures Embedded Messaging Deployments for Messaging for In-App and Web (MIAW). Use when the user needs to create a new embedded messaging deployment from scratch using Connect API with defaults, or update an existing deployment's settings using Metadata API. Produces Connect API request payloads for new deployments and EmbeddedServiceConfig metadata XML for updates. TRIGGER when the user mentions embedded messaging deployment, embedded service deployment, MIAW deployment, messaging widget setup, chat widget configuration, embedded chat deployment, or references a .EmbeddedServiceConfig-meta.xml file. DO NOT TRIGGER when the user is creating a messaging channel (use service-digital-engagement-channel-configure), configuring legacy Live Agent embedded service, or generating the JavaScript code snippet for website embedding.
Transform a user-supplied photo into an expressive minimal zine poster made only from original source-derived illustration, an artistic proposition, emotional tension, visual metaphor, spacious negative space, art-directed high-chroma color, and unconstrained authorial typography. Let wording, language, amount, placement, type voices, scale, direction, legibility, and image interaction follow expression and aesthetic judgment rather than presets. Preserve source orientation by default with a 3:5 portrait output or 5:3 landscape output. Add source-derived distributed supporting accents and a natural isolated-contour option alongside adaptive paper-edge transitions. Support an exact `单色块模式` trigger for one contiguous saturated color field with all remaining forms in neutral ink. Use for authored abstract or editorial reinterpretations that communicate an emotion or idea without embedding, cropping, tracing, or preserving the original photographic material in the final image.
This skill should be used when building data processing pipelines with CocoIndex, a Python library for incremental data transformation. Use when the task involves processing files/data into databases, creating vector embeddings, building knowledge graphs, ETL workflows, or any data pipeline requiring automatic change detection and incremental updates. CocoIndex is Python-native (supports any Python types), has no DSL, and uses version 1.0.0 or later.
Expert guidance for Satori, the library that converts JSX/HTML and CSS into SVG (the engine behind dynamic Open Graph images and social cards). Use whenever writing or debugging Satori markup e.g. authoring JSX for OG images, choosing CSS that Satori actually supports, fixing layout that renders wrong, embedding fonts, rendering emoji or images, or resolving Satori errors like "Expected length unit" or unsupported property issues. Reach for this any time someone renders HTML/CSS to SVG or PNG with Satori, even if they do not name it.
Import CSV or Excel files into seekdb vector database and manage collections. Supports automatic vectorization of specified columns using embedding functions. When users need to: (1) Read and preview Excel files, (2) Import CSV/Excel data into seekdb, (3) Create vector collections from tabular data, (4) Vectorize specific text columns for semantic search, (5) Batch insert product/document data with embeddings, (6) Delete collections, or (7) Access sample data files (sample_products.csv/xlsx) for testing - IMPORTANT: sample files are located in this skill's example-data/ directory, you MUST read this skill file first to get the correct path.
Split text into contextual chunks for RAG/embedding pipelines. Document segmentation and section extraction using window, tfidf, punctuation, or hybrid strategies chosen by intent.
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
Use when planning, debugging, tuning, evaluating, exporting, or deploying public Nemotron `embed`/`rerank` retrieval recipes.
AI/ML APIs, LLM integration, and intelligent application patterns