用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/kortix-ai/suna --skill pdf命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | |
| description | Use for creating, editing, extracting, OCRing, filling, and converting PDF documents. |
| defaultProjectInstall | true |
| defaultProjectInstallOrder | 40 |
pypdf, pdfplumber, pymupdf, pdf2image, pypdfium2, pytesseract, reportlab, and pillow are pre-installed. Run Python files with python3 script.py. Use uv run --with <package> script.py only for a package that is not pre-installed.
from pypdf import PdfReader, PdfWriter
reader = PdfReader("document.pdf")
print(f"Pages: {len(reader.pages)}")
text = "".join(page.extract_text() or "" for page in reader.pages)
Use this for fast inspection. Move to the tool-specific sections below when you need layout-aware extraction, OCR, forms, rendering, or creation.
| Task | Tool | Details |
|---|---|---|
| Convert to Markdown | anydoc | anydoc document.pdf -o out.md — no OCR; scanned PDFs exit 1 |
| Create PDF from scratch | ReportLab | libraries/reportlab.md |
| Read / merge / split / rotate / encrypt | pypdf | — |
| Extract text and tables | pdfplumber | libraries/pdfplumber.md |
| Render pages to images | pypdfium2 | libraries/pypdfium2.md |
| Create/manipulate in JavaScript | pdf-lib | — |
| CLI merge/split/encrypt/optimize/repair | qpdf | libraries/cli-tools.md |
| CLI text extraction | pdftotext | libraries/cli-tools.md |
| CLI image extraction | pdfimages | libraries/cli-tools.md |
| CLI page rendering | pdftoppm | libraries/cli-tools.md |
| OCR scanned PDFs | pytesseract + pdf2image | Convert to images, then OCR |
| Fill PDF forms | pypdf or pdf-lib | form-filling.md |
| Convert PDF to Word | pdf2docx (load docx skill) | See docx skill — Converting PDF to Word |
Form filling: You MUST read form-filling.md before attempting to fill any PDF form.
Design defaults: See skills/design-foundations/SKILL.md for palette, fonts + PDF pairings, chart colors, and core principles (1 accent + neutrals, no decorative imagery, accessibility).
Typography: PDFs embed any TTF font — use distinctive, professional fonts, not system defaults. Download from Google Fonts at runtime, register with ReportLab, and it embeds automatically. See libraries/reportlab.md (Custom Fonts section) and skills/design-foundations/SKILL.md (PDF Pairings table + Font Strategy by Format). Default to a clean sans-serif (Inter, DM Sans, Work Sans).
CJK text: Fonts like Inter and DM Sans only cover Latin glyphs. ReportLab has no automatic font fallback — unregistered scripts render as tofu. Register Noto Sans CJK for Chinese, Japanese, or Korean text. See libraries/reportlab.md (CJK Font Support).
Currency & symbol glyphs: The same Latin-only fonts also lack many currency and symbol glyphs — e.g. ₹ (U+20B9), ₩, ₫, ₴, ﷼. ReportLab and matplotlib render these as tofu with no fallback (matplotlib warns Glyph ... missing from font(s)). Either register a font that includes the glyph (e.g. Noto Sans), or use an ASCII fallback consistently (e.g. Rs for INR) across both charts and PDF body text so they match.
Always set metadata when creating PDFs:
"Kortix" unless the user asks for a different organization or author nameCanvas API: c.setTitle(...), c.setAuthor("Kortix") right after creating the canvas.
SimpleDocTemplate: pass title=..., author="Kortix" as constructor kwargs.
pdf-lib (JS): doc.setTitle(...), doc.setAuthor("Kortix").
Every PDF that includes information from web sources MUST have:
<super> tags, never Unicode superscripts)Each footnote entry must include the actual URL wrapped in an <a href> tag — never omit the URL or substitute a plain-text source name. See libraries/reportlab.md (Source Citations) for the implementation pattern.
All URLs in generated PDFs must be clickable. In ReportLab Paragraph objects, use <a href="..." color="blue"> markup. On the canvas, use canvas.linkURL(url, rect). See libraries/reportlab.md (Hyperlinks).
Never use Unicode subscript/superscript characters in ReportLab PDFs. Built-in fonts lack these glyphs, rendering them as black boxes. Use <sub> and <super> XML tags in Paragraph objects. For canvas text, manually adjust font size and y-offset. See libraries/reportlab.md (Subscripts and Superscripts).
Text extraction: pdftotext is the fastest option for plain text. Use pdfplumber when you need tables or coordinate data — don't use pypdf.extract_text() on large documents, it's slow.
Image extraction: pdfimages extracts embedded images directly and is much faster than rendering whole pages. Only render with pypdfium2 or pdftoppm when you need a visual snapshot of the page layout.
Large PDFs: Process pages individually or in chunks rather than loading the entire document. Use qpdf --split-pages to break up very large files before processing.
Encrypted PDFs: Use pypdf to detect and decrypt (reader.is_encrypted / reader.decrypt(pw)). If you don't have the password, try qpdf --password=X --decrypt. Run qpdf --show-encryption to inspect what protection is applied.
Corrupted PDFs: Run qpdf --check to diagnose structural problems, then qpdf --replace-input to attempt repair.
Verifying generated PDFs: Rendering pages to images (pypdfium2/pdftoppm) only helps if your model can view images. If it can't, verify via text extraction instead — dump page.extract_text() with pypdf and check content, ordering, and that nothing overflowed — and confirm metadata (title, author) is set.
Text extraction fails: If pdfplumber or pdftotext return empty/garbled text, the PDF is likely scanned images. Fall back to OCR (see below).
import pytesseract
from pdf2image import convert_from_path
pages = convert_from_path("scan_output.pdf", dpi=300)
ocr_text = "\n\n".join(
f"--- Page {n} ---\n{pytesseract.image_to_string(pg)}"
for n, pg in enumerate(pages, 1)
)