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.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Dependencies are pre-installed in the sandbox — do NOT pip install, npm install, or apt-get install anything. Just import or invoke directly. The sandbox runs as a non-root user without sudo, so apt-get install ... will fail with a permission error and sudo apt-get ... will fail with sudo: not found. If a CLI tool returns not found, fall back to the equivalent Python library on this page rather than attempting to install it.
python-pptx, markitdown[pptx], Pillow./usr/lib/node_modules): pptxgenjs, react, react-dom, react-icons, sharp. See pptxgenjs.md for the NODE_PATH invocation — without it, node my_script.js will fail with Cannot find module 'pptxgenjs'.read_fileFor any request to read, summarise, analyse, or extract text from a
deck, call read_file directly:
read_file(path="path/to/presentation.pptx")
The harness parses .pptx natively via markitdown and returns slide
text as markdown. Pagination via offset/limit is free (cached).
Do NOT shell out to python -m markitdown or pip install python-pptx for plain reading — that subprocess hop is exactly what
read_file eliminates.
Use the helpers below only when read_file is not enough (visual
overview of slides, raw XML access, editing, or creating from scratch).
| Task | Guide |
|---|---|
| Read / analyze content | read_file(path="presentation.pptx") |
| Visual overview of slides | python scripts/thumbnail.py presentation.pptx |
| Edit or create from template | Read editing.md |
| Create from scratch | Read pptxgenjs.md |
For plain text reading use read_file (see top of skill). Use the
recipes here when you need a visual layout (thumbnails) or surgical
XML access:
# Visual overview of every slide
python scripts/thumbnail.py presentation.pptx
# Raw XML access (rare — for surgical edits, not for reading)
python scripts/office/unpack.py presentation.pptx unpacked/
Read editing.md for full details.
thumbnail.pyRead pptxgenjs.md for full details.
Use when no template or reference presentation is available.
Don't create boring slides. Plain bullets on a white background won't impress anyone. Consider ideas from this list for each slide.
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) |
Every slide needs a visual element — image, chart, icon, or shape. Text-only slides are forgettable.
Layout options:
Data display:
Visual polish:
Choose an interesting font pairing — don't default to Arial. Pick a header font with personality and pair it with a clean body font.
| Header Font | Body Font |
|---|---|
| Georgia | Calibri |
| Arial Black | Arial |
| Calibri | Calibri Light |
| Cambria | Calibri |
| Trebuchet MS | Calibri |
| Impact | Arial |
| Palatino | Garamond |
| Consolas | Calibri |
| Element | Size |
|---|---|
| Slide title | 36-44pt bold |
| Section header | 20-24pt bold |
| Body text | 14-16pt |
| Captions | 10-12pt muted |
margin: 0 on the text box or offset the shape to account for paddingAssume 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.
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.
python -m markitdown output.pptx to inspect contentDo not declare success until you've completed at least one fix-and-verify cycle.
markitdown[pptx] — text extraction (Python; just import).Pillow — thumbnail grids (Python; just import).pptxgenjs — creating from scratch (npm, installed globally; just require('pptxgenjs')).Do NOT pip install or npm install any of these — they are already on PATH in every sandbox.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
The Arbor research-coordinator protocol: the OBSERVE -> IDEATE -> SELECT -> DISPATCH -> DECIDE cycle over a durable Idea Tree. Preloaded automatically on /auto-research sessions. The coordinator never edits code or runs commands — executors do that in isolated worktrees; the coordinator steers the tree with idea_tree / dispatch_experiments / merge_experiment.
日本語の概要は準備中です。原文の説明を表示しています。
The Arbor executor workflow: clone the repo from the git bundle your brief hands you, implement and evaluate exactly ONE hypothesis with the file tools, then report structured results via worker_complete. Preloaded automatically on arbor-executor task workers. Never touch the held-out test split.
日本語の概要は準備中です。原文の説明を表示しています。
Hard-gated ideation for an Arbor research run. Load at the START of every IDEATE round, before drafting any hypothesis. Enforces the PI mindset (mechanism over knob), the four-question first-principles probe, the kill-filter, and the four-line hypothesis format. Ported from Arbor's idea_drafting + first_principles_probe.
日本語の概要は準備中です。原文の説明を表示しています。
DECIDE-phase doctrine for an Arbor research run: when to merge, prune, combine, or finalize; how the held-out merge gate works; and the rule that the final report uses TEST scores. Load before deciding what to do with completed experiments.
日本語の概要は準備中です。原文の説明を表示しています。
Intake for an autonomous research run (Arbor). Use when the user wants to optimize a metric in a repo over many isolated experiments — 'optimize this benchmark', 'improve the model F1 overnight', 'beat the leaderboard'. Discovers the repo/eval/splits, measures the baseline, confirms a Research Contract, then emits a ready-to-send /auto-research command. Does NOT start the run itself.
日本語の概要は準備中です。原文の説明を表示しています。
You MUST use this before any creative work — creating features, building components, drafting documents, designing workflows, or modifying behavior. Explores your human partner's intent, requirements, and design before any implementation begins.
日本語の概要は準備中です。原文の説明を表示しています。