Total 50,907 skills, AI & Machine Learning has 8525 skills
Showing 12 of 8525 skills
Discover and communicate with AI agents on the Agently marketplace. Use this skill when browsing available agents, sending messages via the A2A protocol, or interacting with paid agents using automatic x402 micropayments.
Activate autonomous Ralph Wiggum loop mode for iterative task completion. Use when you have a well-defined task with clear completion criteria that benefits from persistent, autonomous execution.
Structured Autonomy Planning Prompt
Executes the implementation plan from a specification. Loops through plan phases, delegates tasks to specialists, updates phase status on completion. Supports resuming from partially-completed plans.
ChatGPT-style deep research strategy with problem decomposition, multi-query generation (3-5 variations per sub-question), evidence synthesis with source ranking, numbered citations, and iterative refinement. Use for complex architecture decisions, multi-domain synthesis, strategic comparisons, technology selection. Keywords: architecture, integration, best practices, strategy, recommendations, comparison.
Set up and manage phone numbers in Vapi for inbound and outbound voice AI calls. Use when importing Twilio, Vonage, or Telnyx numbers, buying Vapi numbers, or configuring phone numbers for assistants.
Monitor repo changes made by another Claude Code instance, accumulate observations, and deliver a final review on request
Prompt engineering and optimization for AI/LLMs. Capabilities: transform unclear prompts, reduce token usage, improve structure, add constraints, optimize for specific models, backward-compatible rewrites. Actions: improve, enhance, optimize, refactor, compress prompts. Keywords: prompt engineering, prompt optimization, token efficiency, LLM prompt, AI prompt, clarity, structure, system prompt, user prompt, few-shot, chain-of-thought, instruction tuning, prompt compression, token reduction, prompt rewrite, semantic preservation. Use when: improving unclear prompts, reducing token consumption, optimizing LLM outputs, restructuring verbose requests, creating system prompts, enhancing prompt clarity.
Scoped CLAUDE.md memory system that reduces context token spend. Creates directory-level context files, tracks savings via dashboard, and routes agents to the right sub-context.
Implement or modify Ruby code that uses the claude-agent-sdk gem, including query() one-shot calls, Client-based interactive sessions, streaming input, option configuration, tools/permissions, hooks, SDK MCP servers, structured output, budgets, sandboxing, session resumption, Rails integration, and error handling.
Generate videos using ByteDance's Seedance model. It supports text-to-video and image-to-video functions, and calls APIs through the volcengine-ark SDK. This skill is activated when users need to generate videos, create video content, or produce videos based on text or images.
Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.