Abstract This paper documents a multi-platform distribution workflow used to push each title produced by the Practitioner Publishing Stack to seven distribution channels: Google Play Books, Scribd, Academia.edu, Internet Archive, ResearchGate, OSF, and Zenodo. The four components handle: Google Play metadata generation from project structure, per-platform upload checklists with metadata requirements, AI cover-art prompt generation, and store-listing optimization (titles, descriptions, keywords). Together they convert one ready-to-distribute book into seven platform-specific upload payloads. What this deposit contains paper.md — the methodology paper (the citable scholarly artifact) supplementary.zip — bundled working source code for 4 component workflows covered by this paper, each with its own README, Python source, configuration, sample input, CITATION.cff, and LICENSE README.md — entry point CITATION.cff — machine-readable citation LICENSE (MIT for code) and LICENSE-DOCS (CC BY 4.0 for documentation) Production Results Books distributed: 558+ across 7 platforms Average platforms per book: 4-5 (not all books target all platforms; academic papers skip GPB, fiction skips Academia.edu) Distribution lag from compile to first channel: under 24 hours typically Reproducibility Four MIT-licensed Python modules with sample books and sample outputs. Companion Papers This deposit is one of ten flagship records in the Practitioner Publishing Stack series. Each flagship is a methodology paper plus the relevant working source as supplementary material. The series: I. Markdown to multi-format compile pipeline (.docx, .pdf, .epub) with consistent typography. (slug: f01-pub-compile-stack, domain: PUB) II. Detection and removal of AI writing signatures from manuscripts before publication. (slug: f02-aiq-zero-signature-pipeline, domain: AIQ) III. End-to-end pipeline from literature search to Zenodo-published, DOI-indexed academic artifact. (slug: f03-res-research-to-doi, domain: RES) IV. Six python-docx utilities for format normalization, heading conversion, and AI-signature cleanup. (slug: f04-doc-production-pipeline, domain: DOC) V. Visual design system: color tokens, typography, charts, diagrams, and AI cover composition. (slug: f05-vis-leather-and-steel-design-system, domain: VIS) VI. Markdown-driven template engine producing branded spreadsheets and PDF checklists for direct sale. (slug: f06-tpl-spec-to-sellable, domain: TPL) VII. (this paper) — Per-channel specification workflow for distribution across seven publishing platforms. VIII. Course-materials pipeline: markdown syllabus to branded PDF and per-session DOCX. (slug: f08-edu-course-materials, domain: EDU) IX. Seven-phase book production methodology with hard quality gates and 18-day average cycle time. (slug: f09-meta-book-lifecycle, domain: META) X. Architectural overview of an independent publishing operation that produced 558+ titles. (slug: f10-meta-practitioner-publishing-stack, domain: META) Author Ibrahim Anwar (Hibranwar) ORCID: 0009-0006-0425-4923 Wikidata: Q138856145 Web: hibranwar.com Affiliation: PT Hibrkraft Kreasi Indonesia (Cileungsi, Bogor, Indonesia) License The methodology paper, configuration, and sample data are released under CC BY 4.0. The Python source code in supplementary.zip is released under the MIT License. Citation If you use this work, please cite via the DOI minted on this Zenodo record. A machine-readable CITATION.cff ships in the deposit. About the Practitioner Publishing Stack The Practitioner Publishing Stack documents an independent publishing operation by Ibrahim Anwar that produced 558+ titles across nonfiction books, public-domain translations, academic papers, and digital templates, distributed across seven platforms, with a single human as the bottleneck. Average end-to-end cycle time per title: 18 days. Operator headcount: 1.
Ibrahim Anwar (Sat,) studied this question.