2 Repos
Improving content by extracting best practices and identifying common pitfalls through structured workflows.
Distinct from Content Extraction: Focuses on editorial improvement and curation of knowledge rather than raw structural extraction
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Skill Seekers is a toolset for generating large language model knowledge bases, featuring a multi-source content scraper and a dedicated RAG data pipeline. It extracts technical data from documentation, code, and video to create structured assets and configuration files for AI-powered IDE extensions. The project distinguishes itself through the ability to transform raw data into polished tutorials and specialized skills for AI plugin marketplaces. It utilizes abstract syntax tree parsing and optical character recognition to analyze GitHub repositories, PDFs, and video frames, converting these
Uses workflows and presets to improve explanations, extract best practices, and curate common pitfalls.
Cipher is an AI agent orchestration framework and LLM context memory layer. It provides a collaborative AI knowledge base and a context synchronization service that allows AI agents and CLI tools to maintain a persistent, structured memory of project decisions and codebase patterns across different sessions and machines. The system distinguishes itself through a version-controlled context model, using branches and commits to track how project knowledge evolves. It features a hierarchical knowledge store where information is organized as markdown files and can be synchronized between local env
Implements a review workflow to curate and approve codebase information added to the structured memory store.