# A template/ approach to Reproducible Generative Research: Architecture and Ergonomics from Configuration through Publication

**Daniel Ari Friedman** (2026) · *Zenodo*

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.19139090.svg)](https://doi.org/10.5281/zenodo.19139090)

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## Abstract

The reproducibility crisis in computational research is fundamentally structural: research artifacts are scattered across disconnected tools—LaTeX editors, Jupyter notebooks, ad-hoc shell scripts—with no enforced mechanism to keep code, data, and manuscript synchronized. Studies have shown that most published findings are false positives, replication rates in psychology hover around 36%, and only 24% of 1.4 million Jupyter notebooks can be successfully re-executed. Existing tools address fragments of this problem: workflow managers (Snakemake, Nextflow, CWL) orchestrate computation; literate programming systems (Quarto, Jupyter Book, R Markdown, Overleaf, OpenAI Prism) render documents; data versioning tools (DVC) track artifacts—but none enforces cross-cutting quality standards as architectural invariants. `template/` applies the principle of Infrastructure as Code to the research lifecycle, making the manuscript, test suite, and provenance chain version-controlled, deterministically buildable, and independently verifiable. It is built on a Two-Layer Architecture that separates 12 reusable infrastructure subpackages (~150 Python modules, validated by ~3,083 tests) from self-contained project workspaces, connected by an eight-stage build pipeline progressing from environment sanitization through test execution (with a Zero-Mock testing policy enforcing 90% project-level and 60% infrastructure-level coverage via real filesystem operations and subprocess invocations), analysis script invocation, Pandoc/XeLaTeX rendering, SHA-256 cryptographic hashing with steganographic watermarking, structural PDF validation, and LLM-assisted review. A Documentation Duality standard equips every directory with both human-readable `README.md` and machine-readable `AGENTS.md` files, while each infrastructure module additionally carries a `SKILL.md`—a structured skill descriptor aligned with the Model Context Protocol—enabling AI agents to locate and invoke module capabilities without hallucinating API signatures. Scalability is demonstrated across three heterogeneous projects—a gradient descent study (`code_project`, 39 tests), a meta-analysis pipeline (`act_inf_metaanalysis`, 505 tests), and this self-referential architectural analysis (`template`, 65 tests)—achieving 100% pipeline success with zero mock violations. The fact that these words, these metrics, and the figures accompanying them were generated by the very pipeline they describe is itself a demonstration of the system's self-productive capacity: the manuscript is not merely *about* `template/` but *of* it, rendered through the same eight-stage pipeline, validated by the same test suite, and watermarked by the same steganographic layer documented herein. A comparative feature analysis against nine peer tools across fourteen dimensions confirms that `template/` uniquely integrates all eleven distinctive capabilities—testing enforcement, coverage thresholds, cryptographic provenance, steganographic watermarking, multi-project management, AI-agent documentation, agentic skill protocol, interactive TUI, Zero-Mock policy, manuscript rendering, and pipeline orchestration—within a single enforced pipeline. `template/` is open source under the Apache 2.0 License at https://github.com/docxology/template , and is presented as a work in progress.

## Keywords

Zenodo publication

## Artifacts

| Field | Value |
|------|-------|
| **DOI** | [10.5281/zenodo.19139090](https://doi.org/10.5281/zenodo.19139090) |
| **Published** | 2026-03-20 |
| **Version** | v1 |
| **Zenodo record** | https://zenodo.org/records/19139089 |

## Files

- `template_daf_v1_03202026_steganography.pdf` - Zenodo PDF
- `template_daf_v1_03202026.pdf` - Zenodo PDF

## Citation

> Daniel Ari Friedman (2026). *A template/ approach to Reproducible Generative Research: Architecture and Ergonomics from Configuration through Publication*. Zenodo. DOI: 10.5281/zenodo.19139090. URL: https://doi.org/10.5281/zenodo.19139090.

## Related

- Zenodo record: https://zenodo.org/records/19139089
- [Full Bibliography](../../pages/BIBLIOGRAPHY.md) · [All Papers](../README.md)