What problem does it solve? Turning a vague research question into a trustworthy, well-sourced document normally requires hours of searching, reading primary sources, and organizing citations. This Skill automates that workflow: it decomposes a theme into sub-questions, searches the web in both English and Japanese, verifies key claims against primary sources, and produces a single cited Markdown research memo. ## Core Features & Use Cases - Structured deep research: Decomposes a theme into 3-8 sub-questions, investigates each with parallel web searches, and enforces a quality gate (10+ sources across 5+ domains) before writing. - Citation-backed Japanese writing: Integrates model knowledge with search results, attaches [n] citations to key claims, prioritizes primary sources, and follows bundled Japanese technical-writing and anti-AI-slop style references. - Optional saving with assets: Presents the memo for review, then saves it as YYYY-MM-DD_<slug>.md with frontmatter, downloads referenced figures into images/, and validates citation links; --no-save returns the memo inline for use from other skills or non-interactive runs. - Use Case: Ask "deep research して: RAG の評価手法の最新動向" and receive a conclusion-first Japanese memo with numbered references, unresolved questions, and an optional dated file saved to the current directory. ## Quick Start Ask the agent to deep research a topic and write a cited memo, for example: 「LLMエージェントの評価手法について deep research してメモにして」.