Total 55,449 skills, AI & Machine Learning has 9217 skills
Showing 12 of 9217 skills
Discover novel small molecule binders for protein targets using structure-based and ligand-based approaches. Creates actionable reports with candidate compounds, ADMET profiles, and synthesis feasibility. Use when users ask to find small molecules for a target, identify novel binders, perform virtual screening, or need hit-to-lead compound identification.
AI Debugging Collaboration Solution. Convert console.log into HTTP requests to collect logs. After the user completes operations, AI can automatically view and analyze the logs without the need for screenshots or copying console content. Supports Claude Code, OpenCode, Cursor.
NLTK natural language toolkit. Use for NLP.
DeepSeek AI models for coding. Use for code AI.
Setting up Model Context Protocol (MCP) integration between Blockbench and Claude AI for AI-assisted 3D modeling. Use when configuring BlockbenchMCP, connecting Claude to Blockbench, troubleshooting MCP connection issues, or enabling AI-powered model creation and manipulation.
Pay for x402-protected API endpoints with USDC. Use when calling APIs that return HTTP 402 Payment Required, integrating payments into agents, handling x402 payment requirements, building autonomous agents that pay for API access, or discovering paid services via Bazaar. Supports EVM (Base, Ethereum, Avalanche) and Solana networks.
Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
Expert guidance for creating, configuring, and using Claude Code hooks. Use when working with hooks, setting up event listeners, validating commands, automating workflows, adding notifications, or understanding hook types (PreToolUse, PostToolUse, Stop, SessionStart, UserPromptSubmit, etc).
Dynamic orchestration engine that plans multi-step agent work as DAGs with Mermaid visualization.
This skill should be used when creating extensions for Claude Code or OpenCode, including plugins, commands, agents, skills, and custom tools. Covers both platforms with format specifications, best practices, and the ai-eng-system build system.
Use when prompts produce inconsistent or unreliable outputs, need explicit structure and constraints, require safety guardrails or quality checks, involve multi-step reasoning that needs decomposition, need domain expertise encoding, or when user mentions improving prompts, prompt templates, structured prompts, prompt optimization, reliable AI outputs, or prompt patterns.
Autonomous multi-agent task orchestration with dependency analysis, parallel tmux/Codex execution, and self-healing heartbeat monitoring. Use for large projects with multiple issues/tasks that need coordinated parallel execution.