Agent Skills Hub

dajare

Generate high-quality Japanese puns (dajare) based on keywords, topics, or situations. Includes rhyme analysis and contextual humor generation.

debugging-strategies

Language-agnostic debugging framework: scientific method, stack trace analysis, logging strategies, and advanced techniques like Git bisect and rubber ducking.

statistical-analysis

Guided statistical analysis with test selection, assumption checking, power analysis, and APA-formatted reporting for academic and experimental research.

cascade-orchestrator

Advanced workflow orchestration for AI agents, featuring multi-model routing, Codex sandbox iteration, parallel swarm execution, and persistent memory across complex pipelines.

reflect-appworld-failure

Analyze AppWorld task failures to extract specific API patterns and generate actionable playbook bullets with concrete code examples.

tool-use-structured-output

Enforce structured JSON output from Claude models using Bedrock tool_use to eliminate parsing failures and ensure schema compliance.

claude-starter

An AI-powered skill that automatically retrieves relevant project context from your RAG knowledge base for complex coding tasks.

split-pdf

Automated pipeline to download, split, and deeply analyze academic PDFs in structured batches to avoid context window limits and ensure high-quality comprehension.

creating-agents-md

Provides a standardized template and guidelines for creating agents.md files to deliver project-specific context to AI coding assistants.

moai-foundation-core

Foundational architectural principles for MoAI-ADK, featuring TRUST 5, SPEC-First TDD, delegation patterns, and token-efficient agent orchestration workflows.

gtm-mcp

Operate Google Tag Manager via MCP. Handles OAuth, resource discovery, and CRUD operations for tags, triggers, and variables directly from your LLM agent.

doc-sync

Synchronizes and maintains CLAUDE.md and README.md documentation hierarchy across a repository to ensure consistent, just-in-time context for AI agents.