cc_sdk_knowledge_extractor

Extract archive files using 7z CLI. Handles ZIP, RAR, 7z, TAR, TAR.GZ, TAR.BZ2 formats. Extracts to subfolder named after archive. Returns list of extracted files for further processing by file-router. Use when processing compressed archives containing course materials or mixed file types.

Extract MySQL database content to text-readable formats (CSV, JSON, Markdown) for LLM processing and content synthesis. Use when working with MySQL databases that need to be converted to text formats for analysis, synthesis, or inclusion in LLM context windows. Routed from db-router skill.

Extract SQLite database content to text-readable formats (CSV, JSON, Markdown) for LLM processing and content synthesis. Use when working with SQLite databases (.db, .sqlite, .sqlite3) from course materials, datasets, or applications that need to be converted to text formats for analysis, synthesis, or inclusion in LLM context windows. Routed from db-router skill.

Identify database file formats by scanning magic bytes and file signatures. Use FIRST when encountering any unknown database file. Returns format type, version, confidence level, and DBeaver CLI compatibility. Pure identification only - for routing decisions, pass results to db-router.

Route database files to appropriate extraction method based on identification from db-identify. Decides between DBeaver CLI (for supported formats) or db-extractor-* skills (for unsupported formats). Use AFTER db-identify to determine extraction workflow.

Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

Unified file identification and routing for CCKnowledgeExtractor pipeline. Detects file types via magic bytes with extension fallback, returns processor skill to invoke. Use FIRST when processing any unknown file. Handles databases (sqlite, access), PDFs, images (png, jpg, gif, bmp, tiff), HTML, archives (zip, rar, 7z, tar), Office docs (docx, pptx, xlsx), and plain text.

Convert HTML files to Markdown using pandoc. Use when processing HTML files for text extraction, converting web content to readable markdown, or batch converting HTML files in a course/project directory to markdown format for downstream processing.

Extract text from images using pytesseract OCR. Handles PNG, JPG, JPEG, GIF, BMP, TIFF formats. Use when processing image files that may contain text, diagrams with labels, screenshots, or scanned documents. Returns extracted text content.

Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When Claude needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.

Presentation creation, editing, and analysis. When Claude needs to work with presentations (.pptx files) for: (1) Creating new presentations, (2) Modifying or editing content, (3) Working with layouts, (4) Adding comments or speaker notes, or any other presentation tasks

Generate quiz/exam content from validated files. Input is path to __cc_validated_files/ folder containing extracted text. Output is quiz markdown in __ccg_Exam/ folder. Generates multiple choice, short answer, and true/false questions. Use after content extraction pipeline completes to create assessment materials.

Generate structured documentation and summaries from validated course files. Creates comprehensive study guides, topic overviews, and reference documentation. Input is path to __cc_validated_files/ folder. Output is markdown documentation in __ccg_Summary/ folder.

Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas