Redact text from PDF documents for blind review anonymization
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。
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。
Important: All
scripts/paths are relative to this skill directory. Run with:cd {this_skill_dir} && python scripts/...Or use thecwdparameter ofexecute_shell_command.
npm install -g pptxgenjs): creating presentations from scratchsoffice): presentation-to-PDF conversionpdftoppm is unavailable, a Python fallback path may use pdf2image.PATH; if missing, report the dependency issue and stop (do not keep retrying).| Task | Guide |
|---|---|
| Read/analyze content | python -m markitdown presentation.pptx |
| Edit or create from template | Read editing.md |
| Create from scratch | Read pptxgenjs.md |
# Text extraction
python -m markitdown presentation.pptx
# Visual overview
python scripts/thumbnail.py presentation.pptx
# Raw XML
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.
⚠️ 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:
- Overlapping elements (text through shapes, lines through words, stacked elements)
- Text overflow or cut off at edges/box boundaries
- 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)
- Insufficient margin from slide edges (< 0.5")
- Columns or similar elements not aligned consistently
- Low-contrast text (e.g., light gray text on cream-colored background)
- Low-contrast icons (e.g., dark icons on dark backgrounds without a contrasting circle)
- Text boxes too narrow causing excessive wrapping
- 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.
Do not declare success until you've completed at least one fix-and-verify cycle.
Convert presentations to individual slide images for visual inspection:
python scripts/office/soffice.py --headless --convert-to pdf output.pptx
pdftoppm -jpeg -r 150 output.pdf 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 output.pdf slide-fixed
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
Redact text from PDF documents for blind review anonymization
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。
Use this skill when reading sensor data from CSV files, writing simulation results to CSV, processing time-series data with pandas, or handling missing values in datasets.
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。
DC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks.
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。
A library for building, validating, visualizing, and serializing dialogue graphs. Use this when parsing scripts or creating branching narrative structures.
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。
Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a "report", "memo", "letter", "template", or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
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。
Generator economic dispatch and cost optimization for power systems. Use when minimizing generation costs, computing optimal generator setpoints, calculating operating margins, or working with generator cost functions.
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。