Extract text from images and scanned PDFs with support for 100+ languages, table detection, and multiple output formats.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add dkyazzentwatwa/chatgpt-skills --skill ocr-document-processorCompatible with
Supported agents
Handles PNG, JPEG, TIFF, BMP images and multi-page PDFs with per-page or full-document extraction
Supports 100+ languages with auto-detection, language-specific packs, and multi-language document processing
Exports to plain text, Markdown, JSON, HTML, and searchable PDFs with confidence scoring and bounding box data
Includes intelligent preprocessing (deskew, de
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionocr-document-processorExecute the skills CLI command in your project's root directory to begin installation:
epx add dkyazzentwatwa/chatgpt-skills --skill ocr-document-processorFetches ocr-document-processor from dkyazzentwatwa/chatgpt-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/ocr-document-processor
Restart Cursor to activate ocr-document-processor. Access via /ocr-document-processorin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
text-summarizer
dkyazzentwatwa/chatgpt-skills · Productivity · same repo
document-xlsx
vasilyu1983/ai-agents-public · Documents · tag: document
document-docx
vasilyu1983/ai-agents-public · Documents · tag: document
pdf-to-markdown
duc01226/easyplatform · Documents · same category
nano-pdf
steipete/clawdis · Documents · same category
pandoc
plinde/claude-plugins · Documents · same category
ocr-document-processor has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: ocr-document-processor is the kind of skill you can hand to a new teammate without a long onboarding doc.
ocr-document-processor reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in ocr-document-processor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in ocr-document-processor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
ocr-document-processor fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for ocr-document-processor matched our evaluation — installs cleanly and behaves as described in the markdown.
Registry listing for ocr-document-processor matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in ocr-document-processor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added ocr-document-processor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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