onyx-dot-app

pptx

"Use this skill any time a .pptx file is involved in any way — as input, output, or both. This includes: creating slide decks, pitch decks, or presentations; reading, parsing, or extracting text from any .pptx file (even if the extracted content will be used elsewhere, like in an email or summary); editing, modifying, or updating existing presentations; combining or splitting slide files; working with templates, layouts, speaker notes, or comments. Trigger whenever the user mentions \"deck,\" \"slides,\" \"presentation,\" or references a .pptx filename, regardless of what they plan to do with the content afterward. If a .pptx file needs to be opened, created, or touched, use this skill."

onyx-dot-app 31,773 4,378 Updated 1mo ago

Resources

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GitHub

Install

npx skillscat add onyx-dot-app/onyx/pptx

Install via the SkillsCat registry.

SKILL.md

PPTX Skill

Path convention: All commands run from the session workspace (your working directory). Never cd into the skill directory. Prefix all skill scripts with .opencode/skills/pptx/. All generated files (unpacked dirs, output presentations, thumbnails, PDFs, images) go in outputs/.

Quick Reference

Task Guide
Read/analyze content python -m markitdown presentation.pptx
Edit or create from template Read editing.md
Create from scratch Read components.md — tested layout library (default); pptxgenjs.md for raw layouts it doesn't cover
Charts from real data Read charts.md — deck-styled matplotlib PNGs via scripts/chart.py
Icons node .opencode/skills/pptx/scripts/icon.js <name> --color <hex> — see pptxgenjs.md
Lint layout (QA step 0) python .opencode/skills/pptx/scripts/lint.py outputs/output.pptx

Build Order (required)

A complete, text-viable deck must exist in outputs/ before any asset
enhancement.
The worst outcome is a turn that ends with no deck at all.

  1. Draft: full deck — all slides, titles, text content, layout structure —
    written and saved to outputs/<name>.pptx. On the template-editing path
    this means an EARLY first clean+pack (see editing.md): edits
    stranded in outputs/unpacked/ deliver nothing.
  2. Enhance in passes (charts, icons), re-saving the deck after each pass.
  3. Lint + QA last (see QA below).

If time or context is running short at any point, stop enhancing and ship the
current saved deck. Never spend the start of a turn generating or inspecting
assets for a deck that doesn't exist yet.

Reading Source Materials (context discipline)

Read attached/source documents as text (python -m markitdown file.pdf).
Never view_image source pages or figure crops — image reads exhaust the
model context in a handful of pages and the turn dies before the deck is
built. To reuse figures from a source PDF, extract the embedded images
directly — no rendering, no cropping, no visual inspection:

mkdir -p outputs/figs/
pdfimages -png -p source.pdf outputs/figs/fig   # fig-<page>-<n>.png per image
python -c "from PIL import Image; import glob; [print(p, Image.open(p).size) for p in sorted(glob.glob('outputs/figs/*.png'))]"

Pick figures by page number and pixel size (real figures are large; icons and
logos are small), place them directly, and verify them in the rendered-slide
QA pass at the end — never by viewing each extraction.


Choosing a Template (do this first)

Starting from a well-designed template produces far better decks than building from scratch. There are two distinct sources of templates — check both:

# User-uploaded templates (the user's own / brand decks) — list these first
ls user_library/*.pptx attachments/*.pptx 2>/dev/null
# Built-in templates (generic starting points provided by Onyx)
ls /workspace/templates/pptx/*.pptx 2>/dev/null
  • If any templates are found: present them to the user as two clearly labeled groups — "Your uploaded templates" (from user_library/ and attachments/) and "Built-in templates" (from /workspace/templates/pptx/) — listing the user's own templates first. Briefly describe each (use thumbnail.py to preview if helpful), then ask which one to use — or whether to build from scratch — and wait for their answer before building. Never silently pick one: a user's own brand deck and a generic built-in are not interchangeable, and only the user knows which they want. This is one of the few cases where you should pause and ask rather than act autonomously.
  • If none are found: build from scratch, and let the user know they can upload a brand/template .pptx for a more polished, on-brand result next time.

Once a template is chosen, follow editing.md. Use the from-scratch path only when the user has no template or explicitly opts for it — default to the tested layout library (components.md), and fall back to raw pptxgenjs.md for layouts it doesn't cover.


Reading Content

# Text extraction
python -m markitdown presentation.pptx

# Visual overview
python .opencode/skills/pptx/scripts/thumbnail.py presentation.pptx

# Raw XML
python .opencode/skills/pptx/scripts/office/unpack.py presentation.pptx outputs/unpacked/

Editing Workflow

Read editing.md for full details.

  1. Analyze template with thumbnail.py
  2. Unpack → manipulate slides → edit content → clean → pack

Creating from Scratch

Read pptxgenjs.md for full details.

Use only when no template is available or the user explicitly chooses to build from scratch (see Choosing a Template).


Design Ideas

These ideas are for building from scratch. When developing on a chosen template, inherit the template's existing palette, fonts, and layout language — match it, don't redesign it. Skip the palette/font suggestions below and reuse what the template already defines.

Don't create boring slides. Plain bullets on a white background won't impress anyone. Consider ideas from this list for each slide.

Before Starting

  • Pick a bold, content-informed color palette: The palette should feel designed for THIS topic. If swapping your colors into a completely different presentation would still "work," you haven't made specific enough choices.
  • Dominance over equality: One color should dominate (60-70% visual weight), with 1-2 supporting tones and one sharp accent. Never give all colors equal weight.
  • Dark/light contrast: Dark backgrounds for title + conclusion slides, light for content ("sandwich" structure). Or commit to dark throughout for a premium feel.
  • Commit to a visual motif: Pick ONE distinctive element and repeat it — rounded image frames, icons in colored circles, thick single-side borders. Carry it across every slide.

Color Palettes

Choose colors that match your topic — don't default to generic blue. Use these palettes as inspiration:

Theme Primary Secondary Accent
Midnight Executive 1E2761 (navy) CADCFC (ice blue) FFFFFF (white)
Forest & Moss 2C5F2D (forest) 97BC62 (moss) F5F5F5 (cream)
Coral Energy F96167 (coral) F9E795 (gold) 2F3C7E (navy)
Warm Terracotta B85042 (terracotta) E7E8D1 (sand) A7BEAE (sage)
Ocean Gradient 065A82 (deep blue) 1C7293 (teal) 21295C (midnight)
Charcoal Minimal 36454F (charcoal) F2F2F2 (off-white) 212121 (black)
Teal Trust 028090 (teal) 00A896 (seafoam) 02C39A (mint)
Berry & Cream 6D2E46 (berry) A26769 (dusty rose) ECE2D0 (cream)
Sage Calm 84B59F (sage) 69A297 (eucalyptus) 50808E (slate)
Cherry Bold 990011 (cherry) FCF6F5 (off-white) 2F3C7E (navy)

For Each Slide

Every slide needs a visual element — image, chart, icon, or shape. Text-only slides are forgettable. Render deck-styled charts from real data with charts.md; render icons zero-setup with scripts/icon.js (see pptxgenjs.md).

Layout options:

  • Two-column (text left, illustration on right)
  • Icon + text rows (icon in colored circle, bold header, description below)
  • 2x2 or 2x3 grid (image on one side, grid of content blocks on other)
  • Half-bleed image (full left or right side) with content overlay

Data display:

  • Large stat callouts (big numbers 60-72pt with small labels below)
  • Comparison columns (before/after, pros/cons, side-by-side options)
  • Timeline or process flow (numbered steps, arrows)

Visual polish:

  • Icons in small colored circles next to section headers
  • Italic accent text for key stats or taglines

Typography

Choose an interesting font pairing — don't default to Arial. Pick a header font with personality and pair it with a clean body font.

When building from scratch, use only the fonts below — any other font name silently falls back and renders wrong. Available: Inter, Montserrat, Lato, EB Garamond and Fira Code (monospace), plus Calibri, Cambria, Arial, Times New Roman (rendered via metric-compatible substitutes — Carlito/Caladea/Liberation).

When editing a template, this list does not apply — keep the template's own fonts. A template may use fonts not listed here (e.g. Kabel, Garet); these are typically embedded in the file and render correctly even though they aren't installed system-wide. Do not swap them for an installed font — that destroys the template's design. clean.py/pack.py preserve embedded fonts (ppt/fonts/), so they survive the edit cycle.

Header Font Body Font Feel
Montserrat Inter Modern, geometric — strong default for a contemporary deck
Inter Inter Minimal; lean on weight (Bold/Light) for hierarchy
EB Garamond Inter Editorial — elegant serif title over a clean sans body
Lato Lato Professional, corporate-safe
Cambria Calibri Classic Office serif/sans pairing
Arial Black Inter Bold, high-impact headlines

Use Fira Code for code samples or dense numeric/stat blocks.

Element Size
Slide title 36-44pt bold
Section header 20-24pt bold
Body text 14-16pt
Captions 10-12pt muted

Spacing

  • 0.5" minimum margins
  • 0.3-0.5" between content blocks
  • Leave breathing room—don't fill every inch

Avoid (Common Mistakes)

  • Don't repeat the same layout — vary columns, cards, and callouts across slides
  • Don't center body text — left-align paragraphs and lists; center only titles
  • Don't skimp on size contrast — titles need 36pt+ to stand out from 14-16pt body
  • Don't default to blue — pick colors that reflect the specific topic
  • Don't mix spacing randomly — choose 0.3" or 0.5" gaps and use consistently
  • Don't style one slide and leave the rest plain — commit fully or keep it simple throughout
  • Don't create text-only slides — add images, icons, charts, or visual elements; avoid plain title + bullets
  • Don't forget text box padding — when aligning lines or shapes with text edges, set margin: 0 on the text box or offset the shape to account for padding
  • Don't use low-contrast elements — icons AND text need strong contrast against the background; avoid light text on light backgrounds or dark text on dark backgrounds
  • NEVER use accent lines under titles — these are a hallmark of AI-generated slides; use whitespace or background color instead

QA (Required)

Assume there are problems. Your job is to find them.

Your first render is almost never correct. Approach QA as a bug hunt, not a confirmation step. If you found zero issues on first inspection, you weren't looking hard enough.

Layout Lint (run first)

Before any render or vision pass, run the deterministic layout linter — it catches the mechanical defects (off-slide shapes, sub-margin text, text overflow, overlapping text frames, low-contrast explicit colors, unknown fonts) with exact slide/shape references:

python .opencode/skills/pptx/scripts/lint.py outputs/output.pptx
  • Exit 0 with LINT_CLEAN means no findings; nonzero means ERRORs exist.
  • Fix every ERROR before moving on. Review each WARN and fix it unless the layout is genuinely intentional (e.g., a deliberate design overlap).
  • Re-run after each fix batch — it's instant, so lint until clean before spending time on rendering.
  • The linter checks contrast only for explicit solid colors; text over images/gradients is skipped and noted — verify those visually.
  • Content-dense decks (analytical / consulting-style slides with intentionally tight margins) generate many advisory MARGIN warnings under the default profile. For those, lint with --profile dense (relaxes the margin warning from 0.5" to 0.25"); error-level checks are unchanged. Tight margins on a dense analytical slide are a deliberate style, not a defect — don't strip density to silence standard-profile MARGIN warnings.

Content QA

python -m markitdown output.pptx

Check for missing content, typos, wrong order.

When using templates, check for leftover placeholder text:

python -m markitdown output.pptx | grep -iE "xxxx|lorem|ipsum|this.*(page|slide).*layout"

If grep returns results, fix them before declaring success.

Visual QA

⚠️ USE SUBAGENTS — even for 2-3 slides. You've been staring at the code and will see what you expect, not what's there. Subagents have fresh eyes.

Convert slides to images (see Converting to Images), then use this prompt:

Visually inspect these slides. Assume there are issues — find them.

Look for:
- Decorative lines positioned for single-line text but title wrapped to two lines
- Source citations or footers colliding with content above
- Elements too close (< 0.3" gaps) or cards/sections nearly touching
- Uneven gaps (large empty area in one place, cramped in another)
- Columns or similar elements not aligned consistently
- Low-contrast text over images or gradients (the linter can't check these)
- Low-contrast icons (e.g., dark icons on dark backgrounds without a contrasting circle)
- Text boxes too narrow causing excessive wrapping
- Inconsistent styling across slides (fonts, colors, motifs drifting)
- Leftover placeholder content

For each slide, list issues or areas of concern, even if minor.

Read and analyze these images:
1. /path/to/slide-01.jpg (Expected: [brief description])
2. /path/to/slide-02.jpg (Expected: [brief description])

Report ALL issues found, including minor ones.

Verification Loop

  1. Generate slides → Run lint.py → fix every ERROR (and unjustified WARNs)
  2. Re-run lint after each fix batch — it's instant — until clean
  3. Convert to images → Inspect (subagent vision pass for the final aesthetic check)
  4. List issues found (if none found, look again more critically)
  5. Fix issues → re-run lint (one fix often creates another problem), then re-verify affected slides
  6. Repeat until lint is clean and a full visual pass reveals no new issues

Do not declare success until you've completed at least one fix-and-verify cycle.


Converting to Images

Convert presentations to individual slide images for visual inspection:

python .opencode/skills/pptx/scripts/office/soffice.py --headless --convert-to pdf outputs/output.pptx
pdftoppm -jpeg -r 150 outputs/output.pdf outputs/slide

This creates slide-01.jpg, slide-02.jpg, etc.

To re-render specific slides after fixes:

pdftoppm -jpeg -r 150 -f N -l N outputs/output.pdf outputs/slide-fixed

Dependencies

  • pip install "markitdown[pptx]" - text extraction
  • pip install Pillow - thumbnail grids
  • npm install -g pptxgenjs - creating from scratch
  • LibreOffice (soffice) - PDF conversion (auto-configured for sandboxed environments via .opencode/skills/pptx/scripts/office/soffice.py)
  • Poppler (pdftoppm) - PDF to images

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