Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Extract PDF Text
Extract text from PDF files using PyMuPDF. Parse tables, forms, and complex layouts. Supports OCR for scanned documents.
skill openclawclawhub Free
Extract text from PDF files using PyMuPDF. Parse tables, forms, and complex layouts. Supports OCR for scanned documents.
โฌ 0 downloads โ
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, examples.md, ocr.md, troubleshooting.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.2
Provenance
- Publisher
- ivangdavila
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
When to Use
Agent needs to extract text from PDFs. Use PyMuPDF (fitz) for fast local extraction. Works with text-based documents, scanned pages with OCR, forms, and complex layouts.
Quick Reference
TopicFileCode examplesexamples.mdOCR setupocr.mdTroubleshootingtroubleshooting.md
1. Install PyMuPDF First
pip install PyMuPDF Import as fitz (historical name): import fitz # PyMuPDF
2. Basic Text Extraction
import fitz doc = fitz.open("document.pdf") text = "" for page in doc: text += page.get_text() doc.close()
3. Pick the Right Method
PDF TypeMethodText-basedpage.get_text() โ fast, accurateScannedOCR with pytesseract โ slowerMixedCheck each page, use OCR when needed
4. Check for Text Before OCR
def needs_ocr(page): text = page.get_text().strip() return len(text) < 50 # Likely scanned if very little text
5. Handle Errors Gracefully
try: doc = fitz.open(path) except fitz.FileDataError: print("Invalid or corrupted PDF") except fitz.PasswordError: doc = fitz.open(path, password="secret")
Extraction Traps
TrapWhat HappensFixOCR on text PDFSlow + worse accuracyCheck get_text() firstForget to close docMemory leakUse with or doc.close()Assume page orderWrong reading flowUse sort=True in get_text()Ignore encodingGarbled charactersPyMuPDF handles UTF-8
Scope
This skill provides instructions for using PyMuPDF to extract PDF text. This skill ONLY: Gives code examples for PyMuPDF Explains OCR setup when needed Troubleshoots common issues This skill NEVER: Accesses files without user request Sends data externally Modifies original PDFs
Security & Privacy
All processing is local: PyMuPDF runs entirely on your machine No external API calls No data leaves your system
Plain Text
text = page.get_text()
Structured (dict)
blocks = page.get_text("dict")["blocks"] for b in blocks: if b["type"] == 0: # text block for line in b["lines"]: for span in line["spans"]: print(span["text"], span["size"])
JSON
import json data = page.get_text("json") parsed = json.loads(data)
Full Example
import fitz def extract_pdf(path): """Extract text from PDF, with OCR fallback for scanned pages.""" doc = fitz.open(path) results = [] for i, page in enumerate(doc): text = page.get_text() method = "text" # If very little text, might be scanned if len(text.strip()) < 50: # OCR would go here (see ocr.md) method = "needs_ocr" results.append({ "page": i + 1, "text": text, "method": method }) doc.close() return { "pages": len(results), "content": results, "word_count": sum(len(r["text"].split()) for r in results) } # Usage result = extract_pdf("document.pdf") print(f"Extracted {result['word_count']} words from {result['pages']} pages")
Feedback
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Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Docs
- SKILL.md
- examples.md
- ocr.md
- troubleshooting.md