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heavy-file-ingestion

Name: heavy-file-ingestion
Availability: InStock
Author: az9713

Convert heavyweight PDFs, DOCX, PPTX, XLSX, CSV, and TSV files into markdown and per-sheet CSV artifacts with index files.

Updated Apr 17, 2026

Search Tags:#pdf #markdown #spreadsheet #csv #document-processing #token-efficiency #file-conversion

Ready to run

npx skills add https://github.com/az9713/OB1-byoc-enhanced --skill heavy-file-ingestion

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: heavy-file-ingestion
Source: https://github.com/az9713/OB1-byoc-enhanced/tree/main/skills/heavy-file-ingestion
Command: npx skills add https://github.com/az9713/OB1-byoc-enhanced --skill heavy-file-ingestion

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pdfplumber, python-docx, python-pptx, openpyxl, markitdown, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Agents and workflows waste model context and cost when they read large or structured files raw. This skill ensures heavyweight files are converted into compact, deterministic artifacts and a lightweight index before any model reasoning occurs.

Core Features & Use Cases

Convert PDFs, DOCX, PPTX, XLSX, CSV, and TSV into markdown, per-sheet CSVs, and a small index that surfaces structure and quality flags.
Create index.md and index.json with previews, stats, quality warnings, and a recommended next step so the main agent can decide whether to read the artifact or escalate.
Use Case: Normalize a multi-sheet financial workbook into CSVs and a manifest for downstream analysis, or extract a long slide deck into a slide outline and speaker notes for summarization.

Quick Start

Run the bundled Python converter on the target file and then read the generated index.md to decide whether to read the extracted artifacts or escalate to a stronger converter.

Frequently Asked Questions about heavy-file-ingestion

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I convert PDF and spreadsheet files into markdown to save model context?▼

To convert PDFs, DOCX, PPTX, and spreadsheets into markdown, you can run a Python converter that transforms heavyweight files into compact artifacts before model reasoning occurs. This process yields markdown or per-sheet CSVs plus a lightweight index.

What is the best way to normalize an XLSX workbook for downstream agent analysis?▼

Normalizing an XLSX workbook involves converting multi-sheet files into per-sheet CSVs and generating an index manifest. This approach surfaces structure and quality flags so the main agent can decide whether to read the extracted artifacts or escalate.

Does the file conversion process work with PDFs, DOCX, and PPTX files?▼

Yes, the file conversion process works with PDFs, DOCX, and PPTX files, utilizing optional libraries such as pdfplumber, python-docx, and python-pptx. It extracts text, tables, and slide outlines into markdown artifacts.

Can I get a structural index and quality warnings after converting a large CSV?▼

Yes, converting a large CSV or TSV generates an index.md and index.json containing previews, stats, and quality warnings. These outputs include a recommended next step to help your workflow decide whether to process the artifact or escalate.

Do I need pdfplumber and openpyxl installed to extract text from large documents?▼

You need the bundled Python converter for basic extraction, but optional libraries like pdfplumber, python-docx, python-pptx, and openpyxl are recommended for handling complex PDFs, DOCX, PPTX, and XLSX files effectively.

When should I avoid reading raw PDFs and use a file conversion approach instead?▼

You should avoid reading raw PDFs and use file conversion when agents risk wasting model context and cost on large structured files. Converting them first into compact markdown prevents inefficient context usage during deep analysis.