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bytonylee/future-slide

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into a disciplined four-stage slide-generation workflow:

개요

into a disciplined four-stage slide-generation workflow:

README

Future Slide Skill

English | 한국어

Navigation: Workflow | Tightened Slide | Examples | Install | License

A reusable skill bundle for turning:

  1. a reference slide image
  2. user-provided files
  3. a user prompt / deck request

into a disciplined four-stage slide-generation workflow:

  1. Extract DESIGN.md from the reference slide image
  2. Build a persuasive slide plan in JSON
  3. Write page-by-page slide prompts in JSON
  4. Generate page images sequentially from the prompt JSON

This bundle is intentionally modeled after the reason gpt-taste exists in the taste-skill repo: not to add more decoration, but to add stricter enforcement, stronger anti-default rules, and mandatory pre-flight structure so GPT-class models do not skip steps or collapse into generic output.

Why this is split into 4 skills

A single prompt often fails in predictable ways:

  • it starts writing slides before the theme is extracted
  • it mixes design analysis with deck strategy
  • it produces page prompts without a real narrative arc
  • it loses layout consistency across body slides
  • it overfits to the visible text in the reference image instead of the slide design system
  • it stops after writing prompts and never actually renders numbered slide outputs

So this bundle separates responsibilities:

  • slide-design → extract a reusable DESIGN.md
  • gpt-image-slide-plan → decide deck logic, ordering, and persuasion
  • gpt-image-slide-prompt → convert that plan into detailed page prompts
  • gpt-image-slide-render → generate slide images sequentially and save them with page-number filenames

New command families

Use the newer command families when you want to choose the output mode explicitly.

GPT image slide commands

  • $gpt-image-slide → run the full image workflow: design → plan → prompt → render
  • $slide-design → only create DESIGN.md
  • $gpt-image-slide-plan → only create slide_plan.json
  • $gpt-image-slide-prompt → only create slide_prompts.json
  • $gpt-image-slide-render → only render page_1.png ... page_N.png

HTML slide commands

  • $html-slide → run the full HTML workflow: design → plan → prompt → render
  • $slide-design → only create browser-implementable DESIGN.md
  • $html-slide-plan → only create slide_plan.json
  • $html-slide-prompt → only create html_slide_prompts.json
  • $html-slide-render → only build the HTML slide deck

Tightened Slide command

  • $tightened-slide → build a single-file HTML horizontal-swipe deck with locked layouts, strict grid rules, image-slot discipline, and validation

Use the skills in this exact sequence:

1) slide-design

Inputs:

  • reference slide image(s)

Output:

  • one DESIGN.md focused on presentation design, not slide content

2) gpt-image-slide-plan

Inputs:

  • extracted DESIGN.md
  • user files
  • user goal / audience / prompt

Output:

  • deck plan JSON with slide ordering, narrative flow, and evidence mapping

3) gpt-image-slide-prompt

Inputs:

  • DESIGN.md
  • plan JSON
  • supporting files if needed

Output:

  • slide-by-slide prompt JSON with detailed visual/content instructions

4) gpt-image-slide-render

Inputs:

  • DESIGN.md
  • page-level prompt JSON such as slide_prompts.json

Output:

  • final slide images saved sequentially into the workspace, for example:
    • page_1.png
    • page_2.png
    • page_3.png

This step is intentionally separate so generation can:

  • inspect each page one by one
  • preserve deck consistency across outputs
  • save project-bound assets explicitly instead of leaving them in tool cache

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Tightened Slide HTML decks

tightened-slide is an independent HTML deck workflow. Use it when the target is a polished horizontal-swipe presentation rather than generated page images.

It produces:

  • index.html from skills/tightened-slide/assets/template.html
  • an adjacent images/ folder for local deck assets
  • a browser-ready presentation with keyboard navigation and static mode

The skill is intentionally stricter than the general HTML slide workflow:

  • body slides must use the registered S01 to S22 layouts
  • maps and route/location pages should use S08 with the Tightened Map Component
  • images must be assigned to known layout slots before prompting or placement
  • deck language is set explicitly with lang and data-language
  • delivery requires node skills/tightened-slide/scripts/validate-deck.mjs path/to/index.html

Example:

$tightened-slide
Create a 9-page Korean launch deck for a new AI research product.
Use the International Klein Blue theme, include one hero image page, and validate the final HTML.

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Example prompts

Below are concrete example prompts based on the actual way these skills were used for the Samsung Biologics / Hana Securities workflow.

slide-design

Use when you have a reference slide image or reference deck image and want to extract a reusable design system.

Example:

$slide-design [Image #1]

More explicit example:

$slide-design
Extract the design theme from this reference slide image.
Focus on official DESIGN.md output with layout placement, header/body/footer flow,
title page / body page / end page flow, icon usage, infographic cards, and diagram behavior.

gpt-image-slide-plan

Use when you already have DESIGN.md and want to build the storyline and slide sequence from files plus user intent.

Example:

$gpt-image-slide-plan /Users/tonylee/Downloads/하나증권 _보고서.pdf
Write the analysis slide for 'Samsung Biologics' in Korean based on report pdf file.

Expanded full-deck example:

$gpt-image-slide-plan /Users/tonylee/Downloads/하나증권 _보고서.pdf
Create a more detailed full deck in Korean from this equity research report.
Keep the structure analytical and report-native.
Plan title page, body pages, end page, and appendix/disclosure flow.

gpt-image-slide-prompt

Use after planning is complete and you want detailed page-level prompt JSON for slide generation.

Minimal example:

$gpt-image-slide-prompt

More explicit example:

$gpt-image-slide-prompt
Use the current DESIGN.md and slide_plan.json.
Generate strict page-by-page prompt JSON with explicit header/body/footer zoning,
table/chart/card hierarchy, icon rules, and anti-generic constraints.

gpt-image-slide-render

Use after slide_prompts.json exists and you want actual slide images rendered sequentially.

Minimal example:

$gpt-image-slide-render

More explicit example:

$gpt-image-slide-render
Based on @slide_prompts.json, create all slide images 1 by 1 and save them
with the page_number naming rule.

Full-deck example:

$gpt-image-slide-render
Use DESIGN.md and slide_prompts.json.
Render the full deck sequentially and save:
page_1.png ... page_N.png

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Example end-to-end usage

Typical sequence:

$slide-design [reference slide image]
$gpt-image-slide-plan /path/to/report.pdf Create a full Korean research-summary deck.
$gpt-image-slide-prompt
$gpt-image-slide-render

What this bundle optimizes for

  • theme extraction first, content second
  • strong cross-slide consistency
  • persuasive story flow
  • explicit evidence-to-slide mapping
  • reusable layout families
  • body-slide discipline
  • title / body / end-page flow discipline
  • explicit header / body / footer zoning
  • icon / infographic / table / chart role clarity
  • sequential image generation with stable numbering
  • no hallucinated design rules when the reference image is ambiguous

Output artifacts

This bundle includes:

  • skills/slide-design/SKILL.md
  • skills/gpt-image-slide/SKILL.md
  • skills/gpt-image-slide-plan/SKILL.md
  • skills/gpt-image-slide-prompt/SKILL.md
  • skills/gpt-image-slide-render/SKILL.md
  • skills/tightened-slide/SKILL.md
  • templates/DESIGN_TEMPLATE.md

Current skill responsibilities

slide-design

  • extracts design theme, placement rules, header/body/footer flow, title/body/end-page behavior
  • captures icon usage, infographic card logic, table/chart treatment, and diagram behavior

gpt-image-slide-plan

  • builds the storyline and page-family rhythm
  • decides where tables, charts, icon-led modules, or comparison exhibits belong
  • plans split topics across multiple pages when needed

gpt-image-slide-prompt

  • converts the plan into strict per-page prompt JSON
  • makes layout family, zoning, and anti-generic rules explicit for every page

gpt-image-slide-render

  • reads DESIGN.md and prompt JSON
  • renders slide images one by one with Codex native image generation
  • saves final outputs into the project using page-number naming

For a full run, the typical artifact chain is:

  1. DESIGN.md
  2. slide_plan.json
  3. slide_prompts.json
  4. page_1.png ... page_N.png

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Installation

Install with npx skills

Use the Skills CLI from a terminal with Node.js 18+:

npx skills add jyoung105/future-slide-skill

You can also use the repository URL:

npx skills add https://github.com/jyoung105/future-slide-skill.git

Restart Codex after installation so the new skills are discovered.

Manual install into .codex

Download or clone this repository, then copy the skill folders into your Codex skills directory:

mkdir -p ~/.codex/skills
cp -R skills/slide-design ~/.codex/skills/
cp -R skills/gpt-image-slide ~/.codex/skills/
cp -R skills/gpt-image-slide-plan ~/.codex/skills/
cp -R skills/gpt-image-slide-prompt ~/.codex/skills/
cp -R skills/gpt-image-slide-render ~/.codex/skills/
cp -R skills/tightened-slide ~/.codex/skills/

For project-local installation, copy the same folders into:

.codex/skills/

Codex discovers skills from folders that contain SKILL.md, so each copied folder must keep its SKILL.md at the folder root.

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License

Future Slide Skill is released under the Apache License 2.0.

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View this README on GitHub

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