Add Skill: local-document-research-with-traceable-citations

Extracted from: https://github.com/0verL1nk/PaperSage.git
Score: 1.0
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Hermes Pipeline
2026-08-10 17:07:46 +00:00
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# Examples: local-document-research-with-traceable-citations
## Usage Example
```python
# How to use this skill
# Inputs: Local document files (PDF, DOCX, PPTX, XLSX, images, TXT), Configured LLM API endpoint and keys (via .env or settings), Optional web search service config if enabled, Local OCR model cache (downloaded on first use)
# Process: Import documents into a project; files are queued for asynchronous processing. → Convert non-PDF formats (DOCX, PPTX, XLSX) to PDF using native Office or LibreOffice fallback. → Run OCR (PaddleOCR) on PDF pages/images to extract text, page numbers, polygons, and confidence scores.
# Outputs: Project with indexed document library (SQLite metadata + LanceDB vectors), AI answers with verifiable citations to source pages, Evidence preview with page image and OCR highlight polygons, Persistent session history, branches, and long-term memory
```