菜单
Extract text, tables, and images from PDFs. Use when: extracting data from reports; converting PDF tables to CSV; pulling images from presentations; processing research papers; batch converting PDFs to text
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。
基于 SOC 职业分类
| name | pdf-extractor |
| description | Extract text, tables, and images from PDFs. Use when: extracting data from reports; converting PDF tables to CSV; pulling images from presentations; processing research papers; batch converting PDFs to text |
| license | MIT |
| metadata | {"author":"ClawFu","version":"1.0.0","mcp-server":"@clawfu/mcp-skills"} |
Extract text, tables, and images from PDF files using pdfplumber - turn static PDFs into usable data.
| Claude Does | You Decide |
|---|---|
| Structures analysis frameworks | Metric definitions |
| Identifies patterns in data | Business interpretation |
| Creates visualization templates | Dashboard design |
| Suggests optimization areas | Action priorities |
| Calculates statistical measures | Decision thresholds |
pip install pdfplumber pypdf click pandas
# For image extraction:
pip install Pillow
python scripts/main.py text document.pdf
python scripts/main.py text document.pdf --pages 1-5
python scripts/main.py tables report.pdf --output tables.csv
python scripts/main.py tables financial.pdf --page 3
python scripts/main.py images presentation.pdf --output ./images/
python scripts/main.py merge doc1.pdf doc2.pdf --output combined.pdf
python scripts/main.py info document.pdf
python scripts/main.py tables annual-report.pdf --output financials.csv
# Output: financials.csv with all tables found
# Also creates individual CSVs: table_page3_1.csv, table_page5_1.csv
python scripts/main.py batch ./pdfs/ --output ./text/
# Converts all PDFs in folder to .txt files
python scripts/main.py text whitepaper.pdf --pages 1,5-10,15
# Extracts only pages 1, 5-10, and 15
category: automation
subcategory: document-processing
dependencies: [pdfplumber, pypdf, pandas]
difficulty: beginner
time_saved: 4+ hours/week
Run a structured 5-pass finishing audit on any website before launch — scoring visual polish, technical foundation, UX completeness, content quality, and cross-device readiness on 100 points. Use when: **Pre-launch** - Final validation before going live; **Post-redesign** - Verify nothing broke during the overhaul; **Client handoff** - Structured proof that the site is ready; **Quarterly review** - Catch accumulated debt; **Single-pass focus** - Run just Pass 2 after a perf sprint
Use when rewriting AI-generated text to match a specific person's or brand's authentic voice. Use when AI output sounds generic, corporate, or detectable. Unlike generic "humanizers," this skill requires voice analysis input and produces voice-consistent output, not fake imperfections.
Process large codebases (>100 files) using the Recursive Language Model pattern. Orchestrates parallel sub-agents to map-reduce across files without context rot. Use when: analyzing large repositories; auditing security or auth across many files; finding patterns across 50+ files; processing large log files or data dumps
Model best-case, worst-case, and likely revenue scenarios with sensitivity analysis for strategic planning. Use when: building financial forecasts; presenting board scenarios; planning headcount around revenue uncertainty; modeling pricing changes impact; preparing investor updates with upside/downside ranges
Use when analyzing server logs to understand how AI crawlers (GPTBot, ClaudeBot, PerplexityBot) interact with your site. Use when optimizing content placement for LLM retrieval, diagnosing why AI search isn't citing your content, or auditing crawl patterns to find optimization gaps.
Use when optimizing for AI search visibility where individual experts and entities outperform generic brand pages. Use when building cross-platform authority for people, organizations, or products that AI models should recognize and cite.