deep-research

Researches a topic via web search and writes a cited Markdown memo in Japanese.

1|Updated Aug 24, 2026
One-click install
npx skills add https://github.com/mjun0812/skills --skill deep-research-mjun0812
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: deep-research
Source: https://github.com/mjun0812/skills/tree/main/skills/research/deep-research
Command: npx skills add https://github.com/mjun0812/skills --skill deep-research-mjun0812

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

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」.

Frequently Asked Questions about deep-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run a deep research task with cited sources?

Invoke the skill with a research theme, and it decomposes the topic into 3-8 sub-questions, searches the web in English and Japanese, reads primary sources, and writes a Markdown memo where key claims carry [n] citations mapped to a reference list.

What output format does the deep research memo use?

The memo is a single Markdown document in Japanese with a conclusion-first structure, per-topic sections, an unresolved-questions section, and a numbered reference list. When saved, it becomes YYYY-MM-DD_<slug>.md with title, created, updated, and model frontmatter.

Can I use deep research from another skill or non-interactive run?

Yes, pass the --no-save argument. The skill then skips the save confirmation and file creation, returning the memo body directly as the response, which suits calls from other skills, agents, or claude -p style executions.

Does deep research work outside Claude Code?

Yes, the skill explicitly avoids depending on vendor-specific tools. It instructs the agent to use whatever web search and parallel execution mechanisms are available in the current environment.

What are the limitations of this research skill?

It only performs investigation and memo writing; it does not summarize, organize, or integrate the memo into other files. For narrow topics with few sources, it reports the scarcity rather than padding the source count.