SkillHub

sea-doc-summarizer

v2.0.0

Summarize documents in EN/CN/BM/ID with cross-language support. Optimized for Southeast Asian languages.

Sourced from ClawHub, Authored by wms2537

Installation

Please help me install the skill `sea-doc-summarizer` from SkillHub official store. npx skills add wms2537/sea-doc-summarizer

SEA Multilingual Document Summarizer

Summarize documents across English, Chinese, Bahasa Malaysia, and Bahasa Indonesia with cross-language support.

How to Use This Skill

Step 1: Charge billing

POST to the skill endpoint to authorize payment:

POST https://sea-doc-summarizer.swmengappdev.workers.dev/charge
Content-Type: application/json

{"user_id": "<user_id>"}

If successful, you'll receive {"success": true}. If payment fails, you'll receive a payment_url to share with the user.

Step 2: Detect source language

Use these heuristics to detect the document language: - Chinese (zh): More than 30% of characters are CJK (Unicode range u4e00-u9fff) - Bahasa Malaysia (ms): High frequency of words: dan, yang, untuk, dalam, dengan, ini, itu, adalah, telah, akan - Bahasa Indonesia (id): Similar to MS but with specific markers: dari, pada, sudah, belum, bisa, harus - English (en): Default if none of the above match

Step 3: Summarize the document

Using your own capabilities, summarize the document according to the requested style:

Style: brief Provide 3-5 bullet points summarizing the key information.

Style: detailed Provide a comprehensive paragraph summary covering all important details.

Style: action_items Extract action items, deadlines, and next steps as a bullet list.

Cross-language summarization: If the target language differs from the source, translate the summary. For example, a Chinese document can be summarized in English.

Language-specific tips: - For BM/ID documents: Pay attention to formal vs informal register - For CN documents: Handle both Simplified and Traditional Chinese - For mixed-language documents (common in MY/SG): Identify the primary language

Step 4: Extract entities

Also extract named entities from the document: - People names - Company/organization names - Monetary amounts (with currency) - Dates and deadlines - Locations

Output Format

Return the summary as JSON:

{
  "summary": "The summarized text here",
  "key_points": ["Point 1", "Point 2", "Point 3"],
  "entities": [
    {"name": "Petronas", "type": "company"},
    {"name": "RM 1.5 million", "type": "amount"}
  ],
  "source_lang": "ms",
  "word_count": {
    "original": 500,
    "summary": 80
  }
}

Pricing

$0.005 USDT per call via SkillPay.me