pptx

A set of instructions for working with PowerPoint presentation files, including their slides, text, images, tables, charts, and speaker notes.

In plain words
What is it for?
It helps create slides from an outline, extract slide content, edit presentation elements, replace images, and export slides to PDF or images.
Why use it?
It explains how presentations are structured, making it easier to inspect or change a deck without damaging its layout.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/hkuds/deeptutor/pptx
Any agent
npx skills add HKUDS/DeepTutor --skill pptx
Clone the repo
git clone --depth 1 https://github.com/HKUDS/DeepTutor

Made for: Claude Code, Codex.

Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,540 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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.

ModelPer sessionOnce invoked
Fable 5 $0.00076 $0.02540
Opus 5 $0.00038 $0.01270
Sonnet 5 $0.00015 $0.00508
Haiku 4.5 $0.00008 $0.00254

Measured 3d ago against content hash ee60d40ee6ff, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

pptx 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 3d 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.

deeptutor/skills/builtin/pptx/SKILL.md · 221 lines

How it starts

The opening of the file, as written. The whole thing — 221 lines — stays where its author put it; the contents beside it link to each section on GitHub.

pptx

Work with PowerPoint .pptx files using python-pptx (preinstalled). A .pptx is a ZIP of XML parts; python-pptx handles the structure so you rarely touch XML. Drop to raw OOXML only for the few things the library can't express (see Advanced).

Run complete Python source with code_execution in the current workspace dir where uploaded files land. Refer to the deck exactly as the Generated artifacts list names it. Use exec only for a genuinely shell-only command; never put this source in python -c or a heredoc.

Mental model

  • A presentation has slides; each slide is built from a layout; layouts live on slide masters. Layouts define placeholders (title, body, picture, etc.) by idx and type.
  • A slide holds shapes: placeholders, text boxes, pictures, tables, charts.
  • Shapes with text expose .text_frame.paragraphs.runs. A run is the unit that carries formatting (font, size, bold, color).
  • Units are EMU. Use the helpers: from pptx.util import Inches, Pt, Emu.

Read / extract

from pptx import Presentation

prs = Presentation("deck.pptx")
print(len(prs.slides), prs.slide_width, prs.slide_height)  # EMU dims

for i, slide in enumerate(prs.slides, 1):
    print(f"--- slide {i} (layout: {slide.slide_layout.name}) ---")
    for shape in slide.shapes:
        if shape.has_text_frame:
            print(shape.text_frame.text)  # \n-joined paragraphs
        elif shape.has_table:
            for row in shape.table.rows:
                print([c.text for c in row.cells])
    if slide.has_notes_slide:
        notes = slide.notes_slide.notes_text_frame.text
        if notes:
            print("NOTES:", notes)

Iterate slide.placeholders to see placeholder idx / placeholder_format.type. For a fast text-only dump, just collect shape.text_frame.text across slides.

Create from an outline

List the layouts first — indices vary by template. With the default template, layout 0 = Title, 1 = Title+Content, 5 = Title Only, 6 = Blank.

from pptx import Presentation
from pptx.util import Inches, Pt

prs = Presentation()  # or Presentation("template.pptx") to inherit a theme
for idx, lay in enumerate(prs.slide_layouts):
    print(idx, lay.name, [(p.placeholder_format.idx, p.name) for p in lay.placeholders])

# Title slide
s = prs.slides.add_slide(prs.slide_layouts[0])
s.shapes.title.text = "My Deck"
s.placeholders[1].text = "Subtitle"  # idx from the listing above

# Title + bullets
s = prs.slides.add_slide(prs.slide_layouts[1])
s.shapes.title.text = "Agenda"
tf = s.placeholders[1].text_frame
tf.text = "First point"  # first paragraph
for line, lvl in [("Second", 0), ("Sub-point", 1)]:
    p = tf.add_paragraph()
    p.text = line
    p.level = lvl

prs.save("out.pptx")

Always set text via placeholders/shapes — never hand-write bullet glyphs (); indentation/bullets come from the layout via paragraph.level.

Read the full file on GitHub · 221 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.

  1. 3d ago First seen · 221 lines · 76 tokens per session scan A ee60d40ee6ff

Subscribe to this mod's changes

pptx is a skill published in the GitHub repository HKUDS/DeepTutor (38,271 stars, last pushed today), licensed Apache-2.0. It adds 76 tokens to every session and 2,540 once invoked, about $0.0004 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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