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.
Human Infra: docs-as-code knowledge base for human runtime infrastructure, longevity evidence, future-waiting paths, disembodied CNS concepts, and memory-editing boundaries.
A markdown template for taking notes to summarize research papers.
My Personal Blog (Robotics)
Obsidian-first LLM Wiki skill pack with ontology-ready bootstrap, canonical JSONL truth layers, and optional graph projection.
Every paper has an afterlife. SciYard is a research marginalia network and Codex plugin for sharing traceable post-publication insights, reproduction notes, and practical experience.
Local Markdown workspace for technical writing, research notes, security blogs, and static site publishing.
Turning same-topic mixed materials into style-controlled Markdown notes, outlines, knowledge frameworks, and presentation outlines.
The map from the research we admire to the things we built because of it — with receipts.
Deliver deep research with a 5-layer Claude skill for markets, products, competitors, regulations, and opportunities
Sunzi Reading / 孙子读论文 Skill: turn dense academic papers into short, warm, beginner-friendly explanations and reading notes.
Research notes on maintaining and reasoning about LLM context windows across long-lived projects. Speculative ideas, heuristic boundaries, and design sketches without empirical validation.
Avi Loeb paper about 3I/ATLAS
Structured workflow notes for Zn battery electrolyte and interface analysis
A ChatGPT-to-Obsidian capture plugin for AI-assisted learning and research notes.
Bilingual, evidence-led research notes on AI, robotics, and technical strategy.
Stanford AI for Lean Club progress on Erdős problems: papers, frontier notes, visualizer data, and Lean formalization.
Chain-of-density study of 'Recursive Language Models' (Zhang, Kraska & Khattab 2025, MIT CSAIL, arXiv:2512.24601) - five-tier note, locator-verified. The prompt-as-environment paradigm Trellis implements: REPL offloading, recursive sub-calls, 10M+ token inputs.
Chain-of-density study of 'Better Harnesses, Smaller Models: Building 90% Cheaper Agents via Automated Harness Adaptation' (Yang, Zhao, Wu & Kästner 2026, CMU, arXiv:2607.08938) - five-tier note, locator-verified. SLM agents, meta-agent harness optimization.
Our chain-of-density note on 'From Sparse to Dense' (Adams et al. 2023, arXiv:2309.04269) — plus the note-taking methodology every OpenCnid paper repo follows. Sources stay canonical.
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