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Production-grade scaffold for reproducible computational research — 10-stage DAG pipelines, ≥90% test coverage, cryptographic provenance (SHA-256 + steganographic PDF watermarking), multi-project workspace, AI-agent-ready with AGENTS.md / SKILL.md throughout.
Local-first research-agent workflows for defensible formal research outputs, with source-first gates, bounded routing, skill receipts, and delivery guards.
Complete AI-assisted scientific research workflow — literature review, interactive citations, article writing, LaTeX export and presentation. Powered by Claude Code inside VS Code.
ReadR is an Obsidian vault template that organizes academic papers through a four-layer architecture: sources → library → annotations → reviews. Built for Obsidian, inspired by Karpathy's llm-wiki.
A powerful and lightweight deep learning project template built on PyTorch Lightning. It accelerates your development by providing a standardized, convention-based framework, allowing you to focus on your core tasks.
The plain-language framework Dandelion Engineering uses to run exploratory scientific research projects with AI agents. No software to install: a folder structure and instructions in ordinary English.
Governance-ready, AI-aware healthcare research object template built with Quarto. Includes lifecycle structure, governance artefacts, and synthetic demonstration project.
MATLAB/Spyder-style Python template for state-space control-systems research: a general Plant core (x'=f(x,u)) where the robot is one plant. LQR, pole placement, MPC; AI-assisted (Claude Code) workflow.
A starter template for Python-based research projects with a consistent folder layout, linting/type-checking config, editor settings, and a LaTex template for writing up results.