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Ppt Image To Editable Ppt

Community
soulmujoco
ppt-image-to-editable-ppt

Convert PPT slide screenshots or exported slide images into editable PowerPoint decks. Use when Codex needs to extract image/icon/material assets from one or many slide images as separate PNGs, rebuild the slides with editable text boxes, native shapes, and movable picture objects, batch-process multiple page images, and merge the reconstructed pages into a complete .pptx file.

Overview

Publishersoulmujoco
RepositoryEditableImage2PPTSkill
Skill nameppt-image-to-editable-ppt
Stars
71
Forks
6
Bundled files
8
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by soulmujoco on GitHub. Read the source before you install it.

Installation

Install the Ppt Image To Editable Ppt AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/soulmujoco/EditableImage2PPTSkill/tree/main
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/soulmujoco/EditableImage2PPTSkill.git \
  .claude/skills/ppt-image-to-editable-ppt
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ppt Image To Editable Ppt in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ppt Image To Editable Ppt on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ppt Image To Editable Ppt is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

PPT Image To Editable PPT

Overview

Use this skill to turn slide images into a reconstructed, editable PowerPoint deck. The workflow is two-stage: first extract visual materials as PNG assets, then rebuild each page as PPT-native text, shapes, lines, and images.

This skill is for screenshots or exported slide pages, not for editing an existing native .pptx file. If a source .pptx exists, prefer editing that deck directly.

Required Posture

Recreate the slide, do not screenshot it. Text must be editable PowerPoint text except for logos, seals, wordmarks, and decorative calligraphy that are better treated as visual assets. Icons and images must be separate picture objects. Simple frames, cards, circles, separators, and rules should be native shapes/lines.

For Chinese academic slides, preserve institution marks and purple/gray visual systems carefully. Use the original image as the visual reference, not as a full-slide background in the final deck.

Workflow

  1. Create a workspace beside the source images:

    • assets/page_###/ for extracted PNGs
    • layouts/page_###.layout.json for editable reconstruction specs
    • output/ for final PPTX files
    • scratch/ for previews, reports, and temporary files
  2. Inspect each source image:

    • record image dimensions
    • inventory all non-text visual materials
    • inventory all editable text
    • identify repeated templates across pages
  3. Extract visual assets:

    • create an asset manifest JSON
    • run scripts/asset_cropper.py
    • inspect _contact_sheet.png
    • iterate until no obvious visual material is missing
  4. Rebuild each slide:

    • create a layout JSON using source-image pixel coordinates
    • use editable text boxes for ordinary text
    • use native PPT shapes/lines for simple geometry
    • use the extracted PNGs for icons, logos, line art, photos, and complex decoration
    • build PPTX with scripts/build_pptx_from_layout.py
  5. Batch and merge:

    • build representative pages first
    • for a deck, create one layout JSON per page
    • combine layouts with scripts/combine_layouts.py
    • export one final PPTX
  6. QA:

    • run scripts/inspect_pptx.py
    • render or preview the saved PPTX when available
    • compare the preview against the source images
    • report output PPTX path, asset folder path, preview/report paths, and unresolved fidelity differences

Read These References As Needed

  • references/asset-manifest.md: asset crop manifest format and extraction modes.
  • references/layout-json.md: editable PPT layout JSON schema.
  • references/reconstruction-sop.md: full per-slide and batch checklist.

Read asset-manifest.md before writing crop manifests. Read layout-json.md before writing layout JSON. Read reconstruction-sop.md for batch jobs or when the slide is visually dense.

Script Commands

Use the active Python environment. If python-pptx is missing, install it into that environment:

bash
python -m pip install python-pptx

For image work, Pillow and NumPy are required. The Codex bundled workspace Python usually includes them.

Extract assets:

bash
python /path/to/skill/scripts/asset_cropper.py \
  --manifest page_002.assets.json \
  --out-dir assets/page_002 \
  --contact-sheet

Build one or more slides from layout JSON:

bash
python /path/to/skill/scripts/build_pptx_from_layout.py \
  --layout layouts/page_002.layout.json \
  --assets-root . \
  --out output/page_002_editable.pptx

Combine per-page layouts:

bash
python /path/to/skill/scripts/combine_layouts.py \
  --layouts layouts \
  --out layouts/combined.layout.json

Inspect final PPTX:

bash
python /path/to/skill/scripts/inspect_pptx.py \
  --pptx output/deck_editable.pptx \
  --report scratch/quality_report.json

Extraction Decisions

Extract separately:

  • logos, emblems, seals, wordmarks
  • icons and pictograms
  • photos, screenshots, chart screenshots when not reconstructing as data
  • background campus/architecture line art
  • footer/header decorative bands
  • complex ribbons, tabs, badge shapes, paired flourishes
  • reusable blank variants such as blank circles or empty ribbon tabs when useful

Do not extract:

  • normal body text
  • titles, section labels, captions, bullets, numbers that can be rebuilt as text
  • simple rectangles, card frames, circles, and straight rules that can be native PPT shapes

Merge only when separate extraction adds no value, such as a footer band with many tiny decorative fragments or a paired title flourish intended to move together.

Reconstruction Decisions

Use source-image pixel coordinates in layout JSON. Set source_width and source_height to the image size. The builder scales positions to the requested slide size.

Element order matters. Place backgrounds first, then large shapes, then image assets, then text.

Keep text boxes generous. PowerPoint, WPS, and preview renderers can use slightly different font metrics. Prefer wider boxes, explicit line breaks, and modest font-size adjustments over tight text regions.

For repeated page templates, create a reusable layout pattern and only swap text/image paths per page. For highly varied pages, rebuild each page individually.

Validation Standard

A job is done only when:

  • every meaningful visual asset from the source slide is either extracted as a PNG or intentionally rebuilt as a native shape
  • ordinary text is editable in the PPTX
  • PNG assets are independent picture objects and can be moved/replaced
  • final PPTX passes package inspection with no empty media or placeholder text
  • the saved PPTX preview has been visually compared against the source image, or the final response states why preview parity could not be rendered

Final responses should include the final .pptx path, extracted asset root, preview path if generated, QA command/report, and any known differences from the source image.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ppt Image To Editable Ppt AI skill do?

Convert PPT slide screenshots or exported slide images into editable PowerPoint decks. Use when Codex needs to extract image/icon/material assets from one or many slide images as separate PNGs, rebuild the slides with editable text boxes, native shapes, and movable picture objects, batch-process multiple page images, and merge the reconstructed pages into a complete .pptx file.

Why use Ppt Image To Editable Ppt on TypingMind?

Because you install it once and use it with any model. Ppt Image To Editable Ppt is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ppt Image To Editable Ppt in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/soulmujoco/EditableImage2PPTSkill/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ppt Image To Editable Ppt?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ppt Image To Editable Ppt?

As many as you like. As long as a model supports skills, you can use Ppt Image To Editable Ppt with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ppt Image To Editable Ppt AI skill free?

Yes. It is published on GitHub by soulmujoco under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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