dajare
Generate high-quality Japanese puns (dajare) based on keywords, topics, or situations. Includes rhyme analysis and contextual humor generation.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
160 skills found
Generate high-quality Japanese puns (dajare) based on keywords, topics, or situations. Includes rhyme analysis and contextual humor generation.
Validates and coordinates batch study guide operations, preventing errors by enforcing template compatibility, file availability, and source-only policies before agent execution.
CLI tool to bundle repository context, files, and prompts into a one-shot request for advanced AI debugging, refactoring, and code review.
Orchestrate end-to-end quality engineering across CI/CD pipelines, from commit-stage unit testing and shift-left strategies to production-stage synthetic monitoring and compliance gates.
A structured prompting framework to transform casual inputs into professional, modular LLM prompts with persona, context, task, format, and guardrails.
Intelligent strategic planning and requirements gathering with multi-perspective consensus loops and structured deliberation.
A suite of professional tools for auditing, evaluating, chunking, and scaffolding production-ready RAG pipelines within Claude Code.
Foundational guidelines for context engineering: optimizing token budgets, attention mechanics, and system architecture for AI agents.
Master multi-agent orchestration with LangGraph. Build stateful, fault-tolerant AI workflows using supervisor-worker patterns, conditional routing, and advanced state management.
An intelligent gateway that analyzes, scores, and routes user requests across 27 agents, 27 skills, and 14 MCPs to optimize Claude Code execution.
Foundational architectural principles for MoAI-ADK, featuring TRUST 5, SPEC-First TDD, delegation patterns, and token-efficient agent orchestration workflows.
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.