2.6K skills · sorted by relevance
Create Word, PDF, and HTML documents from Markdown, choosing pandoc or ReportLab to suit formatting and layout needs. The workflow covers character handling, output checks, and an alternative generation method when PDF conversion fails.
Set up NVIDIA infrastructure for synthetic data generation on MicroK8s or Azure AKS. Coordinate Kubernetes, inference services, and OSMO workflow execution, with prerequisite checks, deployment validation, capacity planning, and failure investigation before workloads are retried.
Build chat, image generation, and speech transcription features on 0G Compute Network, a distributed GPU marketplace. This skill guides SDK integration, model fine-tuning, response processing for billing, and account funding through code patterns and CLI commands.
Develop a confirmed talk angle and title into a five-act script with speaker notes and timing. Receive a slide-by-slide specification and a completed prompt to paste into Kimi for presentation generation.
Turn reference images into prompts for AI image generation by describing composition, lighting, colors, and materials. Receive a main prompt and a negative prompt that specifies unwanted features, tailored to the image’s visual medium.
Provide backup web search, image search, image downloads, and image generation for other PPT skills when the agent’s native equivalent is missing or fails. Selected images are saved locally for use in presentation files.
Select technologies for AI and machine learning features in .NET 8+ applications. Get task-specific plans or implementation guidance for structured predictions, text generation, document retrieval, tool-using agents, and running pretrained models locally or in production.
Use pre-trained models with Hugging Face Transformers for text generation, translation, image recognition, and speech tasks. Load models, prepare inputs, run predictions, and fine-tune them, meaning further training with your own data.
Develop testable scientific hypotheses from observations, preliminary data, and published evidence. The skill compares competing explanations, defines measurable predictions, proposes experiments, and organizes evidence and decision criteria into a structured research report.
Create synthetic defect images for detector training using clean images and masks that mark defect regions. Guide mask placement, Cosmos fine-tuning, image generation, evaluation, quality refinement, and automatic assignment of provisional labels.
Generate synthetic 3D brain MRI volumes with NV-Generate-CTMR MR-Brain v1, choosing scan types such as T1 or FLAIR. The wrapper records generation settings and output checks for experimental review, with restrictions on clinical and production use.
Set up NVIDIA infrastructure for synthetic data generation on MicroK8s or Azure AKS. Coordinate Kubernetes, inference services, and OSMO workflow execution, with prerequisite checks, deployment validation, capacity planning, and failure investigation before workloads are retried.
Configure speculative decoding on Jetson vLLM servers, letting a smaller model propose tokens for the main model to verify. Adjust memory allocation and benchmark before and after to assess generation speed under low concurrency.
Generate DNA sequences with NVIDIA Evo 2, check their length and alphabet, and save sequence files alongside probabilities and timing metrics. A local deployment also supports extracting numerical outputs from selected internal model layers.
Implement rate limiting for Anima API code generation requests. Use when batching component generation, handling rate limit errors, or optimizing API throughput for large design systems. Trigger with: "anima rate limit", "anima throttling", "anima batch generation".
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Optimize Anima code generation performance with caching, parallelism, and output tuning. Use when reducing generation latency, optimizing batch component generation, or improving generated code quality for production use. Trigger with: "anima performance", "anima slow", "anima optimization", "anima caching".
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Install the Anima SDK and configure authentication for Figma-to-code generation. Use when setting up design-to-code automation, configuring Figma token access, or initializing the @animaapp/anima-sdk for server-side code generation. Trigger with: "install anima", "setup anima", "anima auth", "anima figma token".
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Configure CI/CD pipeline for automated Figma-to-code generation with Anima. Use when automating design-to-code in GitHub Actions, setting up PR-based component generation, or integrating Anima into design handoff workflows. Trigger with: "anima CI", "anima GitHub Actions", "anima automated generation".
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Run a current Adobe Firefly image generation job with prompt approval, response-led polling, artifact custody, and cancellation. Use for approved creative automation. Use when the task requires firefly controlled async generation. Trigger with "generate with Firefly", "Firefly async job", or "Adobe image generation".
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Recommend suitable prompts from 10,000+ Nano Banana Pro image generation prompts based on user needs. Optimized for Nano Banana Pro (Gemini), but prompts also work with Nano Banana 2, Seedream 5.0, GPT Image 1.5, Midjourney, DALL-E, Flux, Stable Diffusion, and any text-to-image AI model. Use this skill when users want to: - Generate images with AI (any model — Nano Banana Pro, Gemini, GPT Image, Seedream, etc.) - Find proven AI image generation prompts and prompt templates - Get prompt recommendations for specific use cases (portraits, products, social media, posters, etc.) - Create illustrations for articles, videos, podcasts, or marketing content - Browse a curated prompt library with sample images - Translate and understand prompt techniques Also available: "ai-image-prompts" skill — a model-agnostic version of this library for universal image generation.
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Guides evaluation of RAG pipeline retrieval and generation quality. Use when evaluating a retrieval-augmented generation system, measuring retrieval quality, assessing generation faithfulness or relevance, generating synthetic QA pairs for retrieval testing, or optimizing chunking strategies.
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Multi-vendor AI image generation with authentication-aware parallel dispatch. Routes to Codex (gpt-image-2 via ChatGPT OAuth) and Pollinations (flux/zimage, free with signup). Gemini provider is present but disabled by default (requires billing). Use for image generation, image creation, visual asset generation, and AI art.
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Configure Simulink models for Embedded Coder (ERT), Simulink Coder (GRT rapid-prototyping), or AUTOSAR code generation. Use when the user asks to generate embedded C or C++ code, run a full build of a model, produce a code generation report, configure a model for production/ECU deployment or rapid-prototyping code, target ARM or x86 hardware, apply MISRA C/C++ compliance (ERT/AUTOSAR only — Simulink Coder does not ship MISRA profiles), or set up GRT, ERT, AUTOSAR, or shared-library targets. Handles target selection, hardware mapping, model hierarchy propagation, and constraint introspection via the configure_for_codegen function. Do NOT use for GRT shared-library variants (grt_malloc.tlc), DDS, or ROS, or for iterative optimization workflows that measure baseline metrics, apply targeted changes, and re-measure to confirm improvement.
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Use when the user has a RAG (Retrieval-Augmented Generation) system and wants to evaluate its quality — separating retrieval issues from generation issues. Also use when the user mentions RAG evaluation, faithfulness checking, hallucination detection in RAG, retrieval quality, chunking optimization, or "is my RAG pipeline working." Outputs a diagnostic matrix that pinpoints whether problems are in retrieval or generation.
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