UI はローカライズ済みです。スキルの紹介と説明文書は選択した言語へ AI が自動翻訳し、コード・コマンド・パス・専門用語は原文のままです。原作者の文書が優先されます。
スキルを探す
データ・研究 · SKILL.md

deep-research

deep-research

Structured multi-step research: search → extract → cross-reference → synthesize with citations.

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

name: deep-research description: "Structured multi-step research: search → extract → cross-reference → synthesize with citations." version: 1.0.0 metadata: echo: tags: [Research, Deep, Analysis, Synthesis, Citations]

Deep Research

Multi-step research workflow that produces cited reports from multiple sources.

Workflow

  1. Decompose — Break the question into 3-5 sub-questions
  2. Search — Run multiple searches per sub-question (diverse keywords)
  3. Extract — Fetch and extract content from top URLs
  4. Cross-reference — Compare claims across sources, flag conflicts
  5. Synthesize — Write structured report with inline citations

Usage

python3 scripts/research_report.py "What are the best practices for LLM agent memory in 2026?"
python3 scripts/research_report.py "Compare FastAPI vs Litestar performance" --depth deep

Output Format

Reports follow this template:

# Research Report: {Topic}

**Date:** YYYY-MM-DD
**Sources consulted:** N

## Summary
2-3 sentence overview of findings.

## Key Findings

### Finding 1
Detail with evidence. [Source 1][1] confirms that...

### Finding 2
...

## Conflicting Information
Where sources disagree, note both positions.

## Conclusion
Actionable synthesis.

## Sources
[1]: https://... — Title
[2]: https://... — Title

Depth Levels

LevelSearchesPages ReadTime
quick2-33-5~30s
normal5-88-12~2min
deep10-1515-25~5min

Combining with Other Skills

  • Use web-search for the search step
  • Use web-extract for the extraction step
  • Use summarize skill for per-page summaries before synthesis
  • Store results with note-taking skill
保存したスキル