401건 · 관련도순
Generate, reference, and conversationally edit short videos with Google's Gemini Omni Flash through the Gemini Developer API or Gemini Enterprise Agent Platform. Use when a task specifically needs Gemini Omni video, multimodal reference roles, time-directed prompting, audio-aware generation, Interactions API state, or a precise comparison with Veo, Nano Banana, consumer Gemini, or gateway routes.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Produce and understand audio with OpenAI request-based audio APIs and audio-capable chat models, including text-to-speech, transcription, translation, multimodal audio input/output, model routing, prompt and performance direction, artifact custody, approval gates, and safety/rights review. Use for non-realtime OpenAI audio production; route continuous live voice agents to the separate realtime voice skill.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when an agent must make TwelveLabs do real video-understanding work: indexing footage, semantic/visual search across an archive, generating descriptions, summaries, chapters, highlights, and tags from video, producing multimodal embeddings, or wiring TwelveLabs into a media-production pipeline (NLE panels, logging, compliance review, metadata). Covers the current model families (Marengo for search/embeddings, Pegasus for video-to-text analysis), the v1.3 Video Understanding API (indexes, assets, tasks, search, analyze, embed), prompt construction for analysis, capability and format limits, pricing/quota math, output quality review (hallucination and timestamp accuracy), and privacy/rights obligations when footage shows real people. Not for generating or editing video pixels — this is analysis and retrieval.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Direct ByteDance Dreamina Seedance 2.0 Standard, Fast, and Mini video production across BytePlus ModelArk and verified gateways. Use for text/image/reference-to-video, native synchronized audio and dialogue, multimodal image-video-audio reference, first/last-frame animation, video editing or extension, model/gateway selection, prompt construction, async task handling, failure recovery, QA, and rights-safe production.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill when an agent needs Google Cloud Vision API for still-image understanding: labels, object localization, OCR, document text, SafeSearch, image properties, crop hints, web detection, batch annotation, Cloud Storage based pipelines, confidence evaluation, privacy, quotas, cost, and QA. Do not use it for Gemini multimodal reasoning, video analysis, image generation, custom model training, product catalog search design, or human reference/authenticity review.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Workflow for paired or integrated single-cell RNA and ATAC analysis with multimodal latent spaces and regulatory interpretation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive patterns for AI-powered document understanding including PDF parsing, OCR, invoice/receipt extraction, table extraction, multimodal RAG with vision models, and structured data output. Use when "document parsing, PDF extraction, OCR, invoice processing, receipt extraction, document understanding, LlamaParse, Unstructured, vision document, table extraction, structured output from PDF, " mentioned.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Azure AI Content Understanding SDK for Python workflow skill. Use this skill when the user needs Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Azure AI Content Understanding SDK for Python workflow skill. Use this skill when the user needs Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
ai-engineer workflow skill. Use this skill when the user needs Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
ai-engineer workflow skill. Use this skill when the user needs Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert guide for Ultra-Low Latency Conversational Voice AI (<300ms), WebRTC bidirectional streaming, OpenAI Realtime API, Gemini Multimodal Live Audio, LiveKit Agents, and Semantic VAD / Panduan ahli AI suara percakapan real-time berlatensi ultra-rendah.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert guide for reverse-engineering UI/UX interactions from screen-recordings and spatial video, extracting animation spring curves, and generating pixel-perfect Tailwind CSS v4 and Framer Motion code / Panduan ahli rekayasa balik interaksi UI/UX dari rekaman layar dan video spasial, ekstraksi kurva pegas animasi, dan pembuatan kode presisi Tailwind CSS v4 serta Framer Motion.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
This skill should be used when the user sends an image and asks to "analyze this image", "describe this picture", "what's in this image", or any request requiring visual understanding of images. Provides image analysis using Zhipu GLM-4.6V multimodal model.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Prompt engineering for production LLMs — structured outputs, evals, RAG, tool workflows, multimodal prompting, and safety. Use when designing, debugging, or shipping prompts.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Designs LLM, agent, responsible-AI, and multimodal evals. Use when measuring quality, fairness, grounding, safety, or judge reliability. Not for test harnesses (qa-agent-testing).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
AI-driven image generation and editing tool for creating high-quality product images. Triggered when users ask to generate images, create product pictures, edit photos, text-to-image, image-to-image, replace backgrounds, transform styles, composite products into scenes, swap models, or create any type of AI-generated visual content. Even if the user does not explicitly say "AI image," this skill should be triggered whenever the request involves creating, modifying, or transforming images.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Guide users to manually instrument Java GenAI applications with otel-util-genai. Use when the user needs OTel GenAI manual instrumentation: chat, Agent/Tool/Workflow/ Retrieval spans, voice/multimodal/smart-glasses telemetry. Works with any OTLP backend. Load from GitHub: alibaba/loongsuite-java/skills/otel-util-genai/
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Protein language models through the EvolutionaryScale `esm` Python SDK. Generate and embed sequences with ESM3 (multimodal sequence, structure and function prompting), extract per-residue and mean-pooled embeddings with ESM C, fold sequences with ESMFold2, and run inference locally or against the Forge and Biohub hosted clients. Use this skill for protein representation learning, variant effect and mutational scanning from likelihoods, sequence generation and inpainting, structure prediction from sequence alone, and embedding features for downstream models. Also trigger on esm, ESM3, ESMC, ESM Cambrian, ESMFold2, `from esm.models`, ESMProtein, GenerationConfig, forge.evolutionaryscale.ai, biohub.ai, or ESM_API_KEY.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when the user wants Agnes AI text, image, or video generation and should execute it through the agnes-ai-cli command line instead of hand-writing raw HTTP requests.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimental_log.md into LaTeX booktabs tables, splices the generated figures from Step 2, and merges everything into the template that already contains Intro + Related Work from Step 3. TRIGGER when the orchestrator delegates Step 4 or when the user asks to "write the methodology and experiments sections" or "fill in the rest of the paper".
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build multimodal AI apps on Clarifai — model marketplace, pipelines, and computer vision plus language workflows.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Official TypeScript SDK for Google Gemini — client setup, text generation, multimodal input, function calling, structured output, streaming, embeddings, context caching, and chat sessions
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Image understanding and document analysis with Claude's multimodal capabilities -- image input formats, PDF processing, multi-image patterns, structured extraction, and token cost estimation
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.