paddleocr-text-recognition

Use this skill when users need to extract text from images, PDFs, or documents. Supports URLs and local files. Returns structured JSON containing recognized text.

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Install skill "paddleocr-text-recognition" with this command: npx skills add aidenwu0209/paddleocr-skills/aidenwu0209-paddleocr-skills-paddleocr-text-recognition

PaddleOCR Text Recognition Skill

When to Use This Skill

Invoke this skill in the following situations:

  • Extract text from images (screenshots, photos, scans, charts)
  • Read text from PDFs or document images
  • Extract text from structured documents (invoices, receipts, forms)
  • Extract text from URLs or local files pointing to images/PDFs

Do not use this skill in the following situations:

  • Plain text files that can be read directly with the Read tool
  • Code files or markdown documents
  • Tasks that do not involve image-to-text conversion

How to Use This Skill

MANDATORY RESTRICTIONS - DO NOT VIOLATE

  1. ONLY use PaddleOCR Text Recognition API - Execute the script python scripts/ocr_caller.py
  2. NEVER use Claude's built-in vision - Do NOT read images yourself
  3. NEVER offer alternatives - Do NOT suggest "I can try to read it" or similar
  4. IF API fails - Display the error message and STOP immediately
  5. NO fallback methods - Do NOT attempt OCR any other way

If the script execution fails (API not configured, network error, etc.):

  • Show the error message to the user
  • Do NOT offer to help using your vision capabilities
  • Do NOT ask "Would you like me to try reading it?"
  • Simply stop and wait for user to fix the configuration

Basic Workflow

  1. Identify the input source:

    • User provides URL: Use the --file-url parameter
    • User provides local file path: Use the --file-path parameter
    • User uploads image: Save it first, then use --file-path
  2. Execute OCR:

    python scripts/ocr_caller.py --file-url "URL provided by user" --pretty
    

    Or for local files:

    python scripts/ocr_caller.py --file-path "file path" --pretty
    

    Save result to file (recommended):

    python scripts/ocr_caller.py --file-url "URL" --output result.json --pretty
    
  3. Parse JSON response:

    • Check the ok field: true means success, false means error
    • Extract text: text field contains all recognized text
    • Handle errors: If ok is false, display error.message
  4. Present results to user:

    • Display extracted text in a readable format
    • If the text is empty, the image may contain no text

IMPORTANT: Complete Output Display

CRITICAL: Always display the COMPLETE recognized text to the user. Do NOT truncate or summarize the OCR results.

  • The script returns the full JSON with complete text content in text field
  • You MUST display the entire text content to the user, no matter how long it is
  • Do NOT use phrases like "Here's a summary" or "The text begins with..."
  • Do NOT truncate with "..." unless the text truly exceeds reasonable display limits
  • The user expects to see ALL the recognized text, not a preview or excerpt

Correct approach:

I've extracted the text from the image. Here's the complete content:

[Display the entire text here]

Incorrect approach:

I found some text in the image. Here's a preview:
"The quick brown fox..." (truncated)

Usage Examples

URL OCR:

python scripts/ocr_caller.py --file-url "https://example.com/invoice.jpg" --pretty

Local File OCR:

python scripts/ocr_caller.py --file-path "./document.pdf" --pretty

Understanding the Output

The script outputs JSON structure as follows:

{
  "ok": true,
  "text": "All recognized text here...",
  "result": { ... },
  "error": null
}

Key fields:

  • ok: true for success, false for error
  • text: Complete recognized text
  • result: Raw API response (for debugging)
  • error: Error details if ok is false

First-Time Configuration

When API is not configured:

The error will show:

CONFIG_ERROR: PADDLEOCR_OCR_API_URL not configured. Get your API at: https://paddleocr.com

Configuration workflow:

  1. Show the exact error message to user (including the URL)

  2. Tell user to provide credentials:

    Please visit the URL above to get your PADDLEOCR_OCR_API_URL and PADDLEOCR_ACCESS_TOKEN.
    Once you have them, send them to me and I'll configure it automatically.
    
  3. When user provides credentials (accept any format):

    • PADDLEOCR_OCR_API_URL=https://xxx.paddleocr.com/ocr, PADDLEOCR_ACCESS_TOKEN=abc123...
    • Here's my API: https://xxx and token: abc123
    • Copy-pasted code format
    • Any other reasonable format
  4. Parse credentials from user's message:

    • Extract PADDLEOCR_OCR_API_URL value (look for URLs with paddleocr.com or similar)
    • Extract PADDLEOCR_ACCESS_TOKEN value (long alphanumeric string, usually 40+ chars)
  5. Configure automatically:

    python scripts/configure.py --api-url "PARSED_URL" --token "PARSED_TOKEN"
    
  6. If configuration succeeds:

    • Inform user: "Configuration complete! Running OCR now..."
    • Retry the original OCR task
  7. If configuration fails:

    • Show the error
    • Ask user to verify the credentials

Error Handling

Authentication failed:

API_ERROR: Authentication failed (403). Check your token.
  • Token is invalid, reconfigure with correct credentials

Quota exceeded:

API_ERROR: API rate limit exceeded (429)
  • Daily API quota exhausted, inform user to wait or upgrade

No text detected:

  • text field is empty
  • Image may be blank, corrupted, or contain no text

Tips for Better Results

If recognition quality is poor, suggest:

  • Check if the image is clear and contains text
  • Provide a higher resolution image if possible

Reference Documentation

For in-depth understanding of the OCR system, refer to:

  • references/output_schema.md - Output format specification
  • references/provider_api.md - Provider API contract

Note: Model version and capabilities are determined by your API endpoint (PADDLEOCR_OCR_API_URL).

Testing the Skill

To verify the skill is working properly:

python scripts/smoke_test.py

This tests configuration and API connectivity.

Source Transparency

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