DeepPaperNote is an agent skill for deep-reading a single paper and generating high-quality Obsidian-style research notes. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
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Updated
May 27, 2026 - Python
DeepPaperNote is an agent skill for deep-reading a single paper and generating high-quality Obsidian-style research notes. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, and more.
A markdown template for taking notes to summarize research papers.
Obsidian-first LLM Wiki skill pack with ontology-ready bootstrap, canonical JSONL truth layers, and optional graph projection.
Research notes on maintaining and reasoning about LLM context windows across long-lived projects. Speculative ideas, heuristic boundaries, and design sketches without empirical validation.
Turning same-topic mixed materials into style-controlled Markdown notes, outlines, knowledge frameworks, and presentation outlines.
Sunzi Reading / 孙子读论文 Skill: turn dense academic papers into short, warm, beginner-friendly explanations and reading notes.
Stanford AI for Lean Club progress on Erdős problems: papers, frontier notes, visualizer data, and Lean formalization.
An experimental research project developing a foundational theory of frameworks — the structures through which the human mind constructs and engages with reality.
前沿物理仿真与智能感知技术调研资料库 | Frontier physics simulation research notes
A framework for clustering research notes
An introduction to actors with working Akka example to demonstrate an actor based approach to concurrency and it's affect of software design on scalability.
Vulnerability Research notes
GitHub Issues and Actions workflow for paper notes, research digests, and AI-assisted recommendations
Lab 137 — a place that both exists and does not exist. Talks, posters & research notes.
SDFI emerges specifically under conditions of recursive self-description and sustained high semantic density, not in ordinary task-oriented interaction.This work is intended as a reference for researchers and system designers thinking about neutrality, termination behavior, and control surfaces in future AI systems.
Notes & experiments on LLMs, open-weight models, multimodal systems, and cloud deployment.
Speculative concept note exploring the "editability surface" - the substrate primitives that allow intelligence to operate within a system and the dynamics that emerge once it does.
Mathematical modeling workspace for MCM-style analysis, report drafting, visualization, and reproducible experiment notes.
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