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GPT-image-2 PPT

by JuneYaooo · JuneYaooo/gpt-image2-ppt-skills

Hand the skill a reference slide and your content — it produces a matching deck using GPT-image-2 layout cloning.

Skill that orchestrates GPT-image-2 to mimic the layout of an existing slide template while substituting your content. Useful when you need to produce decks in a corporate style without designer cycles.

Why use it

Key features

Live Demo

What it looks like in practice

ready

Install

Author repository · Claude Skills documentation

Use Cases

Real-world ways to use GPT-image-2 PPT

Reskin a 10-slide template with new content

👤 Claude Code users ⏱ ~15 min intermediate

When to use: You have a Marketing template and your numbers; need a polished deck by EOD.

Flow
  1. Anchor
    Provide the template slides.✓ Copied
    → Layout captured
  2. Brief
    Supply your bullets / numbers.✓ Copied
    → Content slotted
  3. Generate
    Skill emits matching slides.✓ Copied
    → Deck ready

Outcome: On-brand deck without manual recreation.

Combinations

Pair with other MCPs for X10 leverage

Use Nano Banana for inspiration prompts before cloning

Combine gpt-image2-ppt-skill with nano-banana-pro-prompts-recommend-skill: Use Nano Banana for inspiration prompts before cloning✓ Copied

Tools

What this MCP exposes

ToolInputsWhen to callCost
clone / fill / render (see docs) Three-phase pipeline 1 call

Cost & Limits

What this costs to run

API quota
GPT-image-2 quota
Tokens per call
Image-gen pricing
Monetary
Free skill; image API costs
Tip
Render at lower resolution first to validate layout

Security

Permissions, secrets, blast radius

Credential storage: Image API key in env
Data egress: OpenAI image endpoint

Troubleshooting

Common errors and fixes

Layout drifts on later slides

Re-anchor mid-deck; consistency degrades over long runs

Alternatives

GPT-image-2 PPT vs others

AlternativeWhen to use it insteadTradeoff
Mck-ppt-design-skillYou want consulting-style layouts directlyNo image-model layout cloning

More

Resources

📖 Read the official README on GitHub

🐙 Browse open issues

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