Total 54,890 skills, AI & Machine Learning has 9107 skills
Showing 12 of 9107 skills
Deep concept anatomist that deconstructs any concept through 8 exploration dimensions (history, dialectics, phenomenology, linguistics, formalization, existentialism, aesthetics, meta-philosophy) and compresses insights into an epiphany. Use when user asks to explain, dissect, or deeply understand a concept, term, or idea. Triggers on '解剖概念', '概念解剖', 'explain concept', 'learn concept', '/ljg-learn'. Produces org-mode output.
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.
Use when orchestrating multi-agent teams for parallel work — feature dev, quality audits, research sprints, bug hunts, or any task needing 2+ agents working concurrently
Get a second opinion from leading AI models on code, architecture, strategy, prompting, or anything. Queries models via OpenRouter, Gemini, or OpenAI APIs. Supports single opinion, multi-model consensus, and devil's advocate patterns. Trigger with 'brains trust', 'second opinion', 'ask gemini', 'ask gpt', 'peer review', 'consult', 'challenge this', or 'devil's advocate'.
Analyze contracts for risks, check completeness, and provide actionable recommendations. Supports employment contracts, NDAs, service agreements, and more.
Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.
Router skill for LLMQuant event workflows. Use when the user needs earnings event briefs, M&A tracking, regulatory risk, catalysts, event calendars, or cross-asset event impact.
Guide for building Graph Neural Networks with PyTorch Geometric (PyG). Use this skill whenever the user asks about graph neural networks, GNNs, node classification, link prediction, graph classification, message passing networks, heterogeneous graphs, neighbor sampling, or any task involving torch_geometric / PyG. Also trigger when you see imports from torch_geometric, or the user mentions graph convolutions (GCN, GAT, GraphSAGE, GIN), graph data structures, or working with relational/network data. Even if the user just says 'graph learning' or 'geometric deep learning', use this skill.
Build an AI agent backend with persistent memory: one Rivet Actor per conversation, queued message handling, and streaming LLM responses as realtime events.
Use inside a product repository when the user wants the full MVP built from their BuilderOS spec documents. Triggers on phrases like "build my MVP", "build the app", "execute the roadmap", "start the build", "work through the whole roadmap", "build everything", or any request to implement the entire plan rather than a single task or phase. Requires `docs/prd.md` and `docs/product-roadmap.md` (plus `docs/product-vision.md` and `docs/design.md` for context). Works through every roadmap task in order — implementing, testing, and verifying each before moving on, marking checkboxes and updating the status line — and runs until all tasks are complete and the magic moment works end to end, then initializes git with an initial commit and offers to connect a remote repo.
Distills a jackin❯ roadmap item — plus optional plan files — into a self-contained /goal prompt capped at 4000 characters.
Find Earth2Studio models, data sources, and examples for a weather/climate use case. Do NOT use for writing inference code, downloading data, or installation.