Total 50,650 skills, AI & Machine Learning has 8490 skills
Showing 12 of 8490 skills
How to design, write, test, and distribute AI skills. Use when a user asks how to create a skill, write SKILL.md and references, tune triggers, or prepare a skill for sharing/distribution.
Reads images of receipts, payment receipts, and Furusato Nozei donation receipts and returns structured data. It can be called from other skills or directly by users.
Generate professional Agent Skills for Claude Code and other AI agents. Creates complete skill packages with SKILL.md, references, scripts, and templates. Use when creating new skills, generating custom slash commands, or building reusable AI capabilities. Validates against Agent Skills specification.
Reads images of deduction certificates (life insurance premiums, earthquake insurance premiums, etc.) and returns structured data. It can be called from other skills or directly by users.
AI-powered generation of complete trading strategy code. Uses create_strategy and create_prediction_market_strategy to transform requirements into production-ready Python code. Most expensive AI tool ($1.00-$4.50 per generation). Generates complete Jesse framework strategies with entry/exit logic, position sizing, and risk management. Use after exploring data and optionally generating ideas. ALWAYS test with test-trading-strategies before deploying.
Launch 3 research agents in parallel — market, users, tech — fast answers
Guides creation of best-practice agent skills following the open format specification. Covers frontmatter, directory structure, progressive disclosure, reference files, rules folders, and validation. Use when creating a new skill, authoring SKILL.md, setting up a rules-based audit skill, structuring a skill bundle, or asking "how to write a skill."
[PREREQUISITE] Install and configure Godot MCP server for programmatic scene manipulation via Model Context Protocol. Use when user explicitly requests MCP-based scene building or automation. NOT for manual Godot workflows. Keywords MCP, Model Context Protocol, scene automation, npx, claude_desktop_config.
Parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). Use when fine-tuning large language models with limited GPU memory, creating task-specific adapters, or when you need to train multiple specialized models from a single base.
Build AI-first applications with RAG pipelines, embeddings, vector databases, agentic workflows, and LLM integration. Master prompt engineering, function calling, streaming responses, and cost optimization for 2025+ AI development.
Use when setting up, deploying, or operating vLLM Studio (env keys, controller/frontend startup, Docker services, branch workflow, and release checklists).
Expert-level precision agriculture, farm management systems, crop monitoring, and agtech