nature-image2ppt

nature-image2ppt is a skill for Codex from Yuan1z0825/nature-skills. It costs 119 tokens per session (2,332 once invoked), scanned A, original, Apache-2.0.

A tool that turns slide images, screenshots, scanned PDFs, or image-only PowerPoint files into editable PowerPoint slides. It rebuilds visible elements as separate objects, such as text, shapes, arrows, flowcharts, and diagrams.

In plain words
What is it for?
Use it to recover editable slides from screenshots, scanned documents, image-only PPT or PPTX files, and diagrams.
Why use it?
It removes the need to recreate a slide manually when the original file is only an image or scan. The result can be edited as a presentation instead of remaining a flat picture.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it to recover editable slides from screenshots, scanned documents, image-only PPT or PPTX files, and diagrams.

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Install with agentmods
npx agentmods add skills/yuan1z0825/nature-skills/nature-image2ppt
About the project

Nature Skills is a collection of reusable skills that help AI agents handle academic writing and scientific visualization. Researchers and AI-assisted scholars use it to turn research tasks into repeatable workflows and usable outputs. The catalogue entries are skills from this collection.

Yuan1z0825/nature-skills · 40,913 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Yuan1z0825/nature-skills --skill nature-image2ppt
Clone the repo
git clone --depth 1 https://github.com/Yuan1z0825/nature-skills

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for nature-image2ppt

README.md
[![agentmods](https://agentmods.dev/badge/skills/yuan1z0825/nature-skills/nature-image2ppt/github.svg)](https://agentmods.dev/skills/yuan1z0825/nature-skills/nature-image2ppt)
Your own site
<a href="https://agentmods.dev/skills/yuan1z0825/nature-skills/nature-image2ppt"><img src="https://agentmods.dev/badge/skills/yuan1z0825/nature-skills/nature-image2ppt/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for nature-image2ppt

Your own site · 80×15
<a href="https://agentmods.dev/skills/yuan1z0825/nature-skills/nature-image2ppt"><img src="https://agentmods.dev/badge/skills/yuan1z0825/nature-skills/nature-image2ppt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 119 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,332 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. ✓ AI security review Sonnet 5 · 6 Sept 2026 📄 Read the review Third-party audits
  • Socket warn 23 Aug 2026
  • Snyk warn 23 Aug 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00119 $0.02332
Opus 5 $0.00060 $0.01166
Sonnet 5 $0.00024 $0.00466
Haiku 4.5 $0.00012 $0.00233

Measured 13d ago against content hash 27eb02056403, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

nature-image2ppt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.

The scan reads SKILL.md. This mod also ships 37 executable files (cli/image2ppt/__init__.py, cli/image2ppt/cli.py, cli/image2ppt/runtime/__init__.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/nature-image2ppt/SKILL.md · 211 lines

How it starts

The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Nature Image2PPT

Use this directory as the complete runtime. Run deterministic actions only through:

python <image2ppt-root>/cli/image2ppt/cli.py <command> ...

Use Python 3.10 or later with requirements.txt installed. When a dedicated environment exists, substitute <image2ppt-root>/.venv/bin/python on macOS/Linux or <image2ppt-root>/.venv/Scripts/python.exe on Windows for every python command below. Do not continue after a failed doctor; install only the reported missing dependency, then rerun it.

Do not discover or invoke another Skill, CLI, Prompt, Schema, module, or state machine.

Read the local contracts progressively

Always read references/workflow.md. Read references/runtime-dependencies.md only for setup or doctor failures, and read references/ocr-text-hints-contract.md only when choosing or troubleshooting OCR.

Before writing a page manifest, read references/page-decision-tree.md and references/manifest-schema.md. Add only the references needed by that page:

  • structured or compound page: references/region-decomposition.md and references/object-routing.md;
  • arrows: references/manifest-arrow-extension.md;
  • raster assets or image-backend work: references/assets-provenance-contract.md.

Before accepting or delivering output, read references/qa-contract.md.

Preserve the single source of truth

  • Treat page_jobs.json as the only page-state source.
  • Treat each pages/page_NNN/manifest.json as the only page-content source.
  • Treat deck_manifest.json as the final-assembly source.
  • Use only prepare, run next/dispatch/record/reset/hints/finalize, and the page commands in the local CLI for stateful lifecycle operations.
  • Keep semantic-region evidence in manifest.json.image2ppt_region_decomposition.
  • Never create a second job file, reconstruction plan, OCR normalizer, page controller, packager, or finalize path.
  • Let supplemental QA report failures; never let it mutate lifecycle state.

Read the full file on GitHub · 211 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 13d ago First seen · 211 lines · 119 tokens per session scan A 27eb02056403

Subscribe to this mod's changes

nature-image2ppt is a skill published in the GitHub repository Yuan1z0825/nature-skills (40,913 stars, last pushed 2d ago), licensed Apache-2.0. It adds 119 tokens to every session and 2,332 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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