What is gpt-image-slide-render?

A slide-image rendering workflow that reads a design guide and slide prompts, then creates each presentation page as a PNG image in order.

Use it to turn DESIGN.md and slide prompt JSON into files such as page_1.png, page_2.png, and page_3.png.

It removes the need to generate slide images manually and helps ensure every requested page is saved with a predictable filename.

gpt-image-slide-render — Skill for Claude Code and Codex by bytonylee

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 bytonylee/future-slide --skill gpt-image-slide-render

Clone the repo

git clone --depth 1 https://github.com/bytonylee/future-slide

Made for: Claude Code, 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/bytonylee/future-slide/gpt-image-slide-render.svg)](https://agentmods.dev/skills/bytonylee/future-slide/gpt-image-slide-render)

Your own site

<a href="https://agentmods.dev/skills/bytonylee/future-slide/gpt-image-slide-render"><img src="https://agentmods.dev/badge/skills/bytonylee/future-slide/gpt-image-slide-render.svg" alt="Measured on agentmods" height="20"></a>

Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 835 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.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00036	$0.00835
Opus 5	$0.00018	$0.00417
Sonnet 5	$0.00007	$0.00167
Haiku 4.5	$0.00004	$0.00084

Measured 8d ago against content hash 904cb2957d4c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

gpt-image-slide-render 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 8d ago.

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/gpt-image-slide-render/SKILL.md · 103 lines

How it starts

The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GPT IMAGE SLIDE RENDER — RENDER PAGE IMAGES FROM `DESIGN.md` + PROMPT JSON

You are a slide production operator. Your job is to take:

DESIGN.md
a page-level slide prompt JSON file such as slide_prompts.json

and generate final slide images one page at a time using Codex native image generation.

Primary goal

Produce all requested slide images sequentially and save them into the current project using a stable page-number naming rule such as:

page_1.png
page_2.png
page_3.png

Do not stop after generating only inline previews. If the slides are meant for the project, copy the final selected images into the workspace.

Required workflow

Read DESIGN.md first.
Read the prompt JSON file and confirm slide count and page order.
Generate slides one by one, in slide-number order.
After each generation:
- inspect the generated image
- verify it matches the intended layout family, page family, and major text/content structure
- copy the chosen generated image from Codex's default generated-images directory into the workspace
- save it using the page-number naming rule
Continue until every requested page is generated and saved.
Report the saved file paths.

Hard rules

Use Codex native image generation, not a custom OpenAI SDK runner.
Do not batch all prompts into one generation call.
Do not skip visual inspection between pages.
Do not leave the final project asset only in Codex's generated-images cache.
Do not overwrite unrelated existing files.
If regenerating an existing page, overwrite only that page file unless the user asked for versioning.
Keep page numbering exactly aligned with the prompt JSON.

Prompt-construction rules

When converting each slide prompt entry into an image-generation prompt:

preserve the page family: title, body, end, or appendix
preserve the layout family named in the prompt JSON
preserve header / body / footer zoning explicitly
preserve table-led vs chart-led vs card-led vs diagram-led hierarchy explicitly
preserve icon rules and infographic rules from the JSON
preserve anti-pattern bans

Read the full file on GitHub · 103 lines

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.

8d ago First seen · 103 lines · 36 tokens per session scan A 904cb2957d4c

Subscribe to this mod's changes

gpt-image-slide-render is a skill published in the GitHub repository bytonylee/future-slide (146 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 36 tokens to every session and 835 once invoked, about $0.0002 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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