Total 50,472 skills, AI & Machine Learning has 8470 skills
Showing 12 of 8470 skills
Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design. Not for affinity prediction.
Create or update Claude skills. Use for new skills, skill references, skill scripts, optimizing existing skills, extending Claude's capabilities.
Facilitates structured brainstorming sessions, conducts comprehensive research, and generates creative solutions using proven frameworks. Trigger keywords - brainstorm, ideate, research, SCAMPER, SWOT, mind map, creative, explore ideas, market research, competitive analysis, innovation, problem solving, feature generation
Bootstraps modular Agent Skills from any repository. Clones the source to `sources/`, extracts core documentation into categorized references under `skills/`, and registers the output in the workspace `AGENTS.md`.
Latest AI models reference - Claude, OpenAI, Gemini, Eleven Labs, Replicate
Implements agents using Deep Agents. Use when building agents with create_deep_agent, configuring backends, defining subagents, adding middleware, or setting up human-in-the-loop workflows.
a set of guidelines to build with Botpress's Agent Development Kit (ADK) - use these whenever you're tasked with building a feature using the ADK
Create professional PowerPoint presentations from various sources including web articles, blog posts, and existing PPTX files. Use when creating PPTX, converting articles to slides, or translating presentations.
Configure OpenAI as embedding provider for GrepAI. Use this skill for high-quality cloud embeddings.
Execute codeagent-wrapper for multi-backend AI code tasks. Supports Codex, Claude, and Gemini backends with file references (@syntax) and structured output.
Create agents for financial analysis, investment research, and portfolio management. Covers financial data processing, risk analysis, and recommendation generation. Use when building investment analysis tools, robo-advisors, portfolio trackers, or financial intelligence systems.
Build declarative AI Services with LangChain4j using interface-based patterns, annotations, memory management, tools integration, and advanced application patterns. Use when implementing type-safe AI-powered features with minimal boilerplate code in Java applications.