Skill 詳細
research-paper
Generates full research papers and related academic deliverables.
使用前に確認
自動レビューは関連性のみを確認し、安全性や推奨を保証しません。使用前に出典の説明を読んでください。
SKILL.md
これはレビュー時に保存された抜粋です。完全で最新の内容は外部ソースを確認してください。
--- name: research-paper description: Enterprise-grade autonomous research paper generation skill for AI coding agents — full papers, literature reviews, theses, whitepapers, surveys, policy briefs — with rigorous methodology, statistical validation, multi-style citations (Harvard / APA / IEEE / MLA / Chicago / Nature / arXiv-numeric), and rich visualizations. Activates on slash commands (`/research`, `/paper`, `/literature-review`, `/whitepaper`, `/thesis`, `/survey`, `/policy`) and on natural-language academic-writing requests. Runtime-neutral — works with Claude Code, OpenCode, Cursor, Cline, Codex, Aider, Amp, Antigravity, and 50+ agents via the `npx skills` installer. license: MIT version: 2.4.0 --- # Research Paper A production-grade agent skill that turns any compatible coding agent (Claude Code, OpenCode, Cursor, Cline, Codex, Aider, Amp, Antigravity, and 50+ others) into a **multi-agent research system**: > Orchestrator → Researcher → Methodologist → Analyst → Visualizer > → Writer → Citation engine → Validator → Reviewer → Publisher. It produces full, citation-heavy, visually rich, publication-ready outputs in **arXiv / IEEE / ACM / Nature / Harvard** styles, plus literature reviews, theses, technical whitepapers, survey papers, and policy briefs. This file is the **entry point**. It is intentionally compact. Heavier guidance (instructions, workflows, engines, validators, rubrics) lives in the topic folders below and is loaded **on demand** via Claude Code's filesystem tools (progressive disclosure). --- ## 1. When to activate ### Slash commands (preferred) | Command | What it does | | ---------------------- | -------------------------------------------------- | | `/research <topic>` | Full empirical research paper | | `/paper <topic>` | Same as `/research`, more permissive | | `/literature-review <topic>` | Systematic / scoping / narrative literature review | | `/whitepaper <topic>` | Industry / technical whitepaper | | `/thesis <topic>` | Thesis / dissertation chapter | | `/survey <topic>` | State-of-the-art / survey paper | | `/policy <topic>` | Policy brief or full policy paper | Common options (any command): `--style [harvard|apa|ieee|mla|chicago|nature|arxiv-numeric]`, `--format [arxiv|ieee|acm|nature|harvard|...]`, `--depth [quick|standard|comprehensive]`, `--sources [N]`, `--visualizations [auto|N|none]`, `--audience [academic|technical|executive|general]`. ### Natural-language triggers - "Write a research paper / academic paper / scientific paper on …" - "Do a literature review / systematic review on …" - "Format this draft as IEEE / ACM / arXiv / Nature / Harvard / APA …" - "Write a thesis chapter / dissertation chapter on …" - "Produce a whitepaper / survey paper / policy brief on …" - "Analyze this dataset and write up the findings as a paper." - "Add citations / bibliography / references in `<style>`." - "Peer-review this draft / validate the methodology." ### Do NOT activate for Blog posts, marketing copy, tweets, casual answers, or single-paragraph explanations. Those are handled normally without this skill. --- ## 2. Operating principles (read every time) 0. **Anchor to TODAY's date FIRST.** Before any planning, search, or writing, determine today's actual date — via system clock (`date -u +%Y-%m-%d`), runtime context, or asking the user. **Never default silently to the training-data cutoff.** Year ranges (`--years last-3`) are computed from today, not from the model's training year. Full protocol: `instructions/freshness.md`. 1. **Plan before writing.** Always start with the research plan in `orchestration/pipeline.md`. Never jump into prose. 2. **Progressive disclosure.** Only read the file you need for the current step. Never preload the whole skill. 3. **Evidence fiGitHub で全文を読む (外部ページ)