Overview
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 23 infrastructure subdirectories (20 importable Python packages, ~604 modules, validated by ~7,780 tests) from self-contained project workspaces, connected by a YAML-declared pipeline (12 stages; default full 10)-based 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 the generated public exemplar roster (templates/template_active_inference, templates/template_autoresearch_project, templates/template_autoscientists, templates/template_code_project, templates/template_gold_refinement, templates/template_literature_meta_analysis, templates/template_madlib, templates/template_newspaper, templates/template_prose_project, templates/template_sia, templates/template_template, templates/template_textbook), with representative heterogeneous cases under projects/templates/: optimization (template_code_project, 231 tests), prose (template_prose_project, 120 tests), and AutoResearch readiness (template_autoresearch_project, 296 tests). These guarantee control-positive layouts for code-centric, prose-centric, and retrieval-centric workflows at 90%+ project coverage alongside 60%+ infrastructure gates. All three share identical pipeline stages without cross-project coupling. This manuscript adds a complementary reflexive artifact: authored from projects/templates/template_template (127 tests) as a public exemplar in the same discovered/rendered tree, using the same analysis and render path and injecting counters from repository introspection. The fact that these words, metrics, and figures were generated by the pipeline they describe demonstrates self-documenting capacity: rendered through the DAG, validated without mocks, optionally watermarked. A comparative analysis against nine peer tools across fourteen dimensions positions template/ as integrating fourteen distinctive enforcement capabilities—testing thresholds, cryptographic provenance, steganographic watermarking, multi-project management, MCP-aligned skill descriptors, Zero-Mock policy, orchestration through publication—in one repository. Code is released under the Apache License 2.0 at github.com/docxology/template; the work remains open-ended.
---
Associated artifacts
GitHub release: v1.0.9 (https://github.com/docxology/template_template/releases/tag/v1.0.9)
DOI: https://doi.org/10.5281/zenodo.20419007
Zenodo: https://zenodo.org/records/20419007
PDF SHA-256: 535bd80943d0ae9fd504a926efb41c6b39c3a812a94ea4d51bc974029bca563c
Overview source: Curated paper metadata.
Methods and contributions
Read the source for the full argument, qualifications, and evidence.
Findings and contributions
- Reports 100% pipeline completion for the sampled multi-project runs, with timings described as illustrative.
- The manuscript was itself produced by the pipeline it describes, with metrics injected from repository introspection.
- The comparative analysis positions template/ as integrating fourteen distinctive enforcement capabilities in one repository.
- States that the provenance layer offers SHA-256 tamper detection but not cryptographic non-repudiation, since it lacks private-key signatures.
- Acknowledges the pipeline is single-machine, without native distributed execution, where Snakemake, Nextflow and CWL are superior.
Methods
- Two-Layer Architecture separating shared infrastructure from project workspaces — Describes a repository design where N independent research projects share infrastructure packages without coupling to each other.
- YAML-declared 12-stage build DAG from tests through Pandoc/XeLaTeX rendering — Specifies the pipeline in pipeline.yaml; default full runs use 10 stages and --core-only runs 8.
- Zero-Mock testing policy with 90% project and 60% infrastructure coverage gates — Tests use real filesystem operations and subprocess calls rather than mocks, with coverage thresholds enforced by the pipeline.
- Feature comparison against nine peer tools across fourteen dimensions — Compares template/ with workflow managers, literate-programming systems, DVC, Overleaf and OpenAI Prism on enforcement features.
- Multi-project pipeline runs measuring coverage, timing, integrity and watermarking — Exemplar projects were run through the core pipeline on an Apple Silicon workstation, recording tests passed, durations and steganography timings.
Summary sources: Paper metadata and evidence · Extracted source text.
PDF downloads
Archived files available directly from this site.
- Friedman_2026_Template_535bd809.pdf PDF · 1.33 MiB
- Friedman_2026_Template_57199c03.pdf PDF · 1.29 MiB
- Friedman_2026_Template_b9bc5cf3.pdf PDF · 1.33 MiB
- Friedman_2026_Template_cc674248.pdf PDF · 1.33 MiB · extracted-text source
These files may be different versions or companion documents. The archive does not identify a latest edition.
Citation
Citation metadata follows the unified bibliography.
Catalog details and resources
Related in Computational
Other catalogued works in the same domain.