Total 50,523 skills, AI & Machine Learning has 8481 skills
Showing 12 of 8481 skills
Orchestrates comprehensive cognitive thinking patterns for complex problem-solving. Analyzes tasks to select optimal pattern(s) from foundational, reasoning, creative, metacognitive, specialized, and neurodivergent categories. Chains multiple patterns when needed and validates outputs before responding.
Set which voice pack (character voice) plays for the current chat session. Automatically enables agentskill rotation mode if not already set. Use when user wants a specific character voice like GLaDOS, Peon, or Kerrigan for this conversation.
Provider-agnostic wait-for-change skill that uses the Dumbwaiter MCP server to wait on PR events (GitHub first) via wait.start/status/cancel/await, with progress notifications and durable state.
Generate and edit images using Google's Nano Banana 2 (Gemini 3.1 Flash Image Preview) API. This skill should be used when the user asks to create or modify images, especially when they need fast iteration, explicit aspect-ratio control, or resolution control from 512px to 4K.
This skill should be used when the user asks to "팀 구성해줘", "team assemble", "전문가 팀으로 해줘", "팀으로 해줘", "swarm", "병렬로 전문가 팀", or wants to decompose a complex task into specialist roles executed via TeamCreate. Also triggers when user describes a task clearly benefiting from parallel expert execution.
Smart answering framework that automatically adapts to question types and delivers evidence-based, natural responses.
INVOKE THIS SKILL when working with LangSmith tracing OR querying traces. Covers adding tracing to applications and querying/exporting trace data. Uses the langsmith CLI tool.
Memory health dashboard showing line counts, topic files, capacity, stale entries, and recommendations.
Edit and enhance images and videos with AI via muapi.ai — prompt-based editing, upscaling, background removal, face swap, lipsync, video effects, and more
Comprehensive prompt and context engineering for any AI system. Four modes: (1) Craft new prompts from scratch, (2) Analyze existing prompts with diagnostic scoring and optional improvement, (3) Convert prompts between model families (Claude/GPT/Gemini/Llama), (4) Evaluate prompts with test suites and rubrics. Adapts all recommendations to model class (instruction-following vs reasoning). Validates findings against current documentation. Use for system prompts, agent prompts, RAG pipelines, tool definitions, or any LLM context design. NOT for running prompts, generating content, or building agents.
Build and deploy parallel execution via subagent waves, agent teams, and multi-wave pipelines. Use when the Decomposition Gate identifies 2+ independent actions or when spawning teams. NOT for single-action tasks or non-parallel work.
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.