obsi-concept-distiller
AI를 활용해 핵심 개념을 추출하고, 문맥을 분석하여 지식 베이스(20_Learning)와 양방향으로 연결합니다.
hello-world
A simple example skill that demonstrates the basic structure of a Claude Skill, including scripts, references, and best practices. Use this as a learning template when creating new skills.
skill-creator
効果的なスキルを作成するためのガイド。このスキルは、ユーザーがAIエージェントの機能を専門知識、ワークフロー、またはツール統合で拡張する新しいスキルを作成（または既存のスキルを更新）したい場合に使用します。
using-harness
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
moai-foundation-core
MoAI-ADK's foundational principles - TRUST 5, SPEC-First TDD, delegation patterns, token optimization, progressive disclosure, modular architecture, agent catalog, command reference, and execution rules for building AI-powered development workflows
non-linear
Uncertainty-aware non-linear reasoning system with recursive subagent orchestration. Triggers for complex reasoning, research, multi-domain synthesis, or when explicit commands `/nlr`, `/reason`, `/think-deep` are used. Integrates think skill (reasoning), agent-core skill (acting), and MCP tools (infranodus, exa, scholar-gateway) in recursive think→act→observe loops. Uses coding sandbox for execution validation and maintains deliberate noisiness via NoisyGraph scaffold. Supports `/compact` mode for abbreviated outputs and `/semantic` mode for rich exploration.
huggingface-tokenizers
Use when "tokenizers", "HuggingFace tokenizer", "BPE", "WordPiece", or asking about "train tokenizer", "custom vocabulary", "tokenization", "subword", "fast tokenizer", "encode text"
test-nice-guy
Always responds politely with a fixed greeting and closing line.
quantum-memory
Manage persistent quantum memories across sessions. Use for storing, retrieving, organizing, and building upon past learnings and insights.
aws-strands
Build AI agents with Strands Agents SDK. Use when developing model-agnostic agents, implementing ReAct patterns, creating multi-agent systems, or building production agents on AWS. Triggers on Strands, Strands SDK, model-agnostic agent, ReAct agent.
scenario-runner-capture
Implement deterministic Scenario Runner + capture outputs for agents
prompt-engineering
Use this skill when you writing commands, hooks, skills for Agent, or prompts for sub agents or any other LLM interaction, including optimizing prompts, improving LLM outputs, or designing production prompt templates.
cli-router
Routes tasks to locally installed CLI tools using semantic matching. Triggers on tasks requiring shell commands, file operations, code search, data processing, visualization, or external tool invocation. Uses cli-index for semantic routing.
llm-models-reference
Reference guide for LLM model IDs, capabilities, pricing, and provider endpoints. Use when selecting a model, comparing provider capabilities, or validating model IDs for {{PROJECT_NAME}}.
ai-agent-orchestrator
Эксперт по оркестрации AI агентов. Используй для multi-agent systems, agent coordination, task delegation и agent workflows.
prompt-engineer
Expert prompt engineering for Claude 4 models (Sonnet 4.5). Use when crafting prompts, optimizing AI responses, implementing chain-of-thought, or improving prompt clarity and effectiveness. Specializes in Claude-specific techniques and best practices.
forging-skills
Prevents skill atrophy by periodically halting for user code writing and review. Use when senior engineers want to stay hands-on while leveraging agentic AI.
51-execute-quality-150
[51] EXECUTE. Commitment to maximum quality work with 150% coverage. Use when you need the highest quality output for critical tasks, complex problems, important decisions, or when standard work isn't enough. Triggers on "maximum quality", "150% mode", "full quality", "critical task", or when you explicitly want AI to work at its best.
claude-code-hooks
Implement Claude Code hooks for deterministic control over agent behavior. Use when creating custom hooks for notifications, auto-formatting, logging, feedback, permissions, or lifecycle events.
mcp-builder
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).
agentic-orchestration
Defines the three-layer architecture for the "Agentic Framework" - a meta-layer that surrounds an Application Layer with a Skills Layer in between, providing production-grade controls for AI agents. Use this skill when designing, explaining, or implementing agentic systems that require robust orchestration, domain capabilities, and safety controls.
