Heavy File Ingestion For Codex

SkillFiles & storage

Use in Codex when a user asks to read, analyze, summarize, or extract from a heavyweight file such as PDF, DOCX, PPTX, XLSX, CSV, or TSV. Convert the file into markdown or CSV first with the bundled script, generate a lightweight index, and only spend model tokens on the compressed artifact.

Then ask your AI: use the Heavy File Ingestion For Codex skill

Details

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add it as a step in a pipeline you build on Ahel, or connect Ahel to Claude, ChatGPT, Cursor, Claude Code or Codex and ask your AI to use it.

What this skill tells your AI

The instructions your AI receives, as published by natebjones-projects/ob1 in skills/heavy-file-ingestion/variants/codex/SKILL.md and read by Ahel’s review.

Problem

Codex can run local commands and inspect files, so direct ingestion of bulky documents is usually the wrong move. Convert first, index second, reason last.

Trigger Conditions

  • The user asks to read or summarize a heavyweight document or spreadsheet
  • The file is large, structured, or expensive enough that raw ingestion is wasteful
  • The task would be better served by markdown, CSV, or a quick file map

Process

  1. Do not open the raw heavyweight file as your first move if a deterministic conversion path exists.
  2. Run the bundled converter from this skill directory:
python scripts/convert_heavy_file.py /absolute/path/to/file.ext
  1. If the environment is clean and needs packages, prefer:
uv run \
  --with pdfplumber \
  --with python-docx \
  --with python-pptx \
  --with openpyxl \
  python scripts/convert_heavy_file.py /absolute/path/to/file.ext
  1. Read index.md first, not the original file.
  2. Follow the index recommendation:
    • read_extracted_artifact: inspect the generated markdown or CSV
    • cheap_model_or_stronger_converter: retry with a better deterministic tool or use a cheaper model on the extracted artifact only
    • manual_review: tell the user the deterministic route failed and propose the next cheapest fallback
  3. Use expensive model context only after the file has already been compressed into a smaller artifact.

Client Rules

  • Keep the main model out of raw PDFs, decks, and spreadsheets whenever possible.
  • Use the generated .ob1/ folder as the working directory for follow-up analysis.
  • For spreadsheets, reason from the CSV per sheet plus the workbook manifest.
  • For presentations, reason from the slide outline before asking for a deeper pass.

Bundled References

  • references/open-source-stack.md explains the tool choices and fallback tiers.

Signals

GitHub stars
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Forks
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Last commit
Oct 2026
Advanced
Item type
skill
Key
heavy-file-ingestion-codex
Source
github.com/natebjones-projects/ob1