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Convert RL, MARL, LLM, and LLM Agent papers into Chinese or English presentation decks, slide outlines, speaker notes, figure explanations, and defense/report structures.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Search, plan, and organize literature for RL, MARL, LLM, and LLM Agent research. Use for finding papers, building related-work maps, identifying baselines, benchmark provenance, citation gaps, and recent work tracking.
Build, audit, and organize citation evidence for RL, MARL, LLM, and LLM Agent manuscripts. Use for related work matrices, citation gaps, DOI/BibTeX checks, baseline provenance, benchmark provenance, and Nature-style support for claims.
Prepare Data Availability, Code Availability, Model Availability, Prompt Availability, and reproducibility statements for RL, MARL, LLM, and LLM Agent manuscripts.
Help legally obtain, organize, and archive academic papers, PDFs, BibTeX, supplementary files, code links, and benchmark documents for RL, MARL, LLM, and LLM Agent research. Do not bypass paywalls or access controls.
Create, revise, or audit Nature-style scientific figures for RL, MARL, LLM, and LLM Agent papers. Use for Python/R plotting, training curves, ablations, benchmark bars, architecture diagrams, agent workflow figures, trajectory visualizations, and publication export QA.
Build a repeatable literature discovery, scoring, reading, and archiving pipeline for RL, MARL, LLM, and LLM Agent research. Use for daily/weekly paper tracking, topic watchlists, benchmark monitoring, and research-note automation.
| name | nature-paper2ppt |
| description | Convert RL, MARL, LLM, and LLM Agent papers into Chinese or English presentation decks, slide outlines, speaker notes, figure explanations, and defense/report structures. |
| version | 2.0.0-agent-rl |
Deck structure:
1. Title
2. Motivation
...
For each slide:
- Slide title:
- On-slide text:
- Visual suggestion:
- Speaker notes:
Do not overload slides with paragraphs. Do not present benchmark numbers without explaining protocol and baselines.