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Pptx Posters

OrganizationPopular
K-Dense-AI
pptx-posters

Create and audit editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. Use when the requested deliverable is a PowerPoint research/conference poster and exact physical, printer, accessibility, provenance, and package-security checks are required.

Overview

PublisherK-Dense-AI
Repositoryclaude-scientific-writer
Skill namepptx-posters
Stars
2.4K
Forks
273
Bundled files
20
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.

  • 20 bundled files

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

  • Open source

    Published by K-Dense-AI on GitHub. Read the source before you install it.

Installation

Install the Pptx Posters 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.
  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/K-Dense-AI/claude-scientific-writer.git /tmp/claude-scientific-writer
mkdir -p .claude/skills
cp -r /tmp/claude-scientific-writer/skills/pptx-posters .claude/skills/pptx-posters
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Pptx Posters 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 Pptx Posters 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 Pptx Posters 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.

PPTX posters

Scope

Use this skill only when the requested source/deliverable is an editable PowerPoint poster. Do not route an unspecified poster request here merely because PowerPoint is available.

Version 2.0 generates a real one-slide .pptx from strict local JSON. It does not use HTML conversion, external templates, schematic/image-generation services, API keys, environment files, network requests, or mandatory figure styles.

Hard gates

Stop instead of guessing when any gate is unmet:

  1. The author has not supplied exact poster content and source records.
  2. Any claim, number, citation, author, affiliation, funding statement, figure, license, or QR target is unresolved.
  3. Current conference and printer requirements are not confirmed.
  4. Author approval is not bound to the current manifest content hash.
  5. An asset is remote, outside the manifest directory, unhashed, or unapproved.
  6. An input is .pptm, contains macros/external relationships/OLE/embedded files, or is an untrusted template.
  7. The requested workflow needs PowerPoint to be opened or executed automatically.
  8. A script reports a package, layout, DPI, contrast, or output-plan blocker.

Never fabricate missing material or leave a plausible placeholder. Drafts fail closed.

Install exact generation dependencies

From the skill directory:

bash
uv venv
uv pip install "python-pptx==1.0.2" "Pillow==12.3.0" "lxml==6.1.1"

Generation requires exactly:

text
python-pptx==1.0.2
Pillow==12.3.0
lxml==6.1.1

All CLIs use lazy optional imports, so python -B scripts/<tool>.py --help works without these packages. Use -B to avoid bytecode artifacts.

Establish requirements before layout

Record these separately:

  • physical trim width/height and orientation;
  • bleed on each edge;
  • safe margin inside trim;
  • PowerPoint canvas width/height;
  • uniform physical-artboard/canvas print scale;
  • conference maximum dimensions and delivery format;
  • printer trim, bleed, margin, scaling, color-mode, and proof requirements;
  • final-output font and raster-DPI thresholds, each labeled as a heuristic or tied to an exact source.
  • required font faces, workstation availability, embedding permission, and the substitution/proof workflow.

There is no universal poster size. Microsoft currently limits each custom PowerPoint dimension to 1–56 inches and uses one size for all slides. If the physical artboard is larger, use a proportional canvas only when the printer confirms scaling.

Read references/poster_layout_design.md.

Build the manifest

Copy assets/poster_manifest_template.json into the project. The template is deliberately invalid until every replacement token, false confirmation, and draft approval is resolved.

Follow references/manifest_spec.md and references/poster_content_guide.md.

The manifest requires:

  • exact source IDs for document metadata, every element, and every asset;
  • author_verified: true on every source;
  • author_approved: true on every element and asset;
  • local PNG/JPEG paths and lowercase SHA-256 hashes;
  • exact provenance and license/permission for every optional image;
  • approved alt text and, when needed, a source-bound native long description;
  • explicit reading order and design rectangles;
  • visible exact fallback URL/text for every local QR image;
  • confirmed conference/printer rules;
  • declared sRGB contrast pairs and redundant data encoding;
  • approval bound to canonical manifest content.

To obtain the content hash after all non-approval fields pass:

bash
python -B scripts/validate_manifest.py poster.json \
  --print-content-hash

Give that exact manifest and hash to the author. Then set approval.status to approved, record approver and offset-aware timestamp, and copy the hash. Any non-approval edit invalidates approval.

Validate the approved manifest and local assets:

bash
python -B scripts/validate_manifest.py poster.json

Audit assets and palette before generation

bash
python -B scripts/inventory_images.py poster.json \
  --output poster.assets.json

python -B scripts/check_palette.py poster.json \
  --output poster.palette.json

python -B scripts/plan_export.py poster.json \
  --output poster.export-plan.json

Effective DPI is pixels divided by final placed inches, not image metadata DPI. The inventory fully decodes bounded images and blocks EXIF/XMP/comments and embedded text/application metadata; strip those offline, then rehash and reapprove the asset. Contrast uses WCAG 2.2 sRGB mathematics; applying those values to a physical poster is a design target, not a standalone conformance claim. Keep color-redundant labels, markers, shapes, patterns, or line styles.

If the printer requires CMYK, the plan blocks print-readiness until a printer-approved conversion/profile and proof exist. Do not claim that a native PowerPoint PDF is CMYK-compliant.

Read references/poster_design_principles.md.

Generate the PPTX

Use a new output path:

bash
python -B scripts/generate_poster.py poster.json \
  --output poster.pptx \
  --report poster.generation.json

Generation:

  • creates a new blank presentation; it never loads a user template;
  • sets the approved canvas before adding content;
  • uses one native title placeholder, native text boxes, and local pictures;
  • preserves image aspect ratio with contain fitting;
  • disables text auto-shrink;
  • adds elements in approved reading order;
  • writes approved picture alt descriptions and explicit text language to PresentationML;
  • does not embed fonts, audio, video, OLE, ActiveX, links, or other media;
  • removes default printer-settings binary data and normalizes package timestamps;
  • inspects the package before and after the alt-text patch;
  • refuses overlaps, out-of-bounds shapes, low final font size/DPI, unsafe packages, and existing destinations.

It renders exact manifest text. It does not compose, summarize, research, or correct scientific content.

Run final technical audits

bash
python -B scripts/inspect_pptx.py poster.pptx \
  --output poster.package.json

python -B scripts/check_layout.py poster.pptx \
  --manifest poster.json \
  --output poster.layout.json

The package inspector reads bounded ZIP metadata and selected XML only. It never extracts members or opens/executes the presentation. It rejects:

  • every non-.pptx extension, including .pptm;
  • packages outside the bounded one-slide generator profile;
  • macro/VBA, ActiveX, custom UI, OLE, embedded, executable, and binary parts;
  • every external relationship, including remote linked images and hyperlinks;
  • unsafe/duplicate ZIP paths, symlinks, encryption, oversized expansion, and excessive compression ratios;
  • malformed or entity-bearing inspected XML;
  • missing internal relationship targets.

Read references/pptx_security.md.

Manual PowerPoint and accessibility gate

Automation cannot certify accessibility, text rendering, or scientific accuracy. In a fully patched PowerPoint:

  1. Open only the generated and technically clean file.
  2. Run Review > Check Accessibility.
  3. Inspect the Reading Order pane and object names.
  4. Review every alt text and native long description.
  5. Test keyboard and screen-reader navigation.
  6. Confirm fonts are installed/licensed; check embedding choices, substitution, glyphs, equations, overflow, contrast, and all edges.
  7. Verify that color is never the only encoding.
  8. Test every QR code and its visible fallback URL/text.
  9. Obtain author sign-off on all content and citations.

Microsoft's 18 pt slide recommendation is not a universal poster minimum. Evaluate font size at final physical output using the manifest's labeled basis and proofs.

Export and print

Use the approved export plan. When PDF is required, export from the reviewed PowerPoint using Standard/high print quality rather than Minimum size.

Independently verify the PDF:

  • page/artboard dimensions, orientation, trim, and bleed;
  • one-page output if required;
  • fonts, clipping, glyphs, equations, and image resampling;
  • tags, reading order, alt text, language, and links;
  • RGB/CMYK conversion and physical color proof;
  • conference naming, file-size, and upload rules.

Print a reduced-scale proof and obtain the printer's required proof. Re-run all checks after any change.

Use assets/poster_quality_checklist.md for release sign-off.

Bundled CLIs

  • validate_manifest.py — strict content/provenance/approval validator.
  • generate_poster.py — exact-pinned local PPTX generator.
  • inspect_pptx.py — non-executing ZIP/XML security inspector.
  • check_layout.py — bounds, overlap, reading-order, and final-font checker.
  • inventory_images.py — asset hash/metadata/effective-DPI manifest.
  • check_palette.py — WCAG contrast and heuristic palette report.
  • plan_export.py — dimensions, scale, fonts, color, media, export, and print preflight.

References

  • references/manifest_spec.md
  • references/poster_content_guide.md
  • references/poster_design_principles.md
  • references/poster_layout_design.md
  • references/pptx_security.md
  • references/security_validation.md
  • references/source_ledger.md

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 Pptx Posters AI skill do?

Create and audit editable scientific posters in macro-free PowerPoint (.pptx) from author-approved local content and assets. Use when the requested deliverable is a PowerPoint research/conference poster and exact physical, printer, accessibility, provenance, and package-security checks are required.

Why use Pptx Posters on TypingMind?

Because you install it once and use it with any model. Pptx Posters 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 Pptx Posters in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/K-Dense-AI/claude-scientific-writer/tree/main/skills/pptx-posters. 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 Pptx Posters?

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 Pptx Posters?

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

Is the Pptx Posters AI skill free?

Yes. It is published on GitHub by K-Dense-AI 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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