Enforce complexity, linting, tests, and CI so AI-written code stays decoupled, tractable, and commit-blocked until quality gates pass.

Event based MS Windows python-script, which: hides own window, de-crap-ifies, flattens directory structure, cleans tvseries-episode release, checks for completeness, decides if wanted quality is met, scans for E-AC3-codec audio-streams, speeds transcoding/encoding up by converting just the audio stream leaving video and subtitles untouched in the container, manages parts of the MEDE8ER's needed meta-data, pre-post-processes, launches post-processing by calling nzbToMedia, streamlines failed-downloads management for torrent downloads, optimizes thereby my SickRage collection of tvseries daily workflow and is started by Deluge's basic, standard Execution-plugin on account of it's limited functionality in extending needed, extra arguments being set to inform the post-processing workers.

This is a meta-framework for teams using Cursor AI to streamline development workflows. It provides structured prompts, workflows, and guidelines to ensure consistent, high-quality code generation and debugging.

[meta] better development: CSS workflows, Firebase development, code quality, real testing, parallel exploration, documentation verification, and token-efficient codegen

Project-Meta is an intelligent content-generation system powered by Meta AI. It automates the creation, optimization, and structuring of digital content across multiple formats. Designed for developers, marketers, and creators, Project-Meta delivers fast, consistent, and high-quality outputs using advanced AI workflows.

A comprehensive framework that guides AI systems to process unstructured code feedback and meta-feedback, producing prioritized, actionable improvement lists with confidence scoring and quality assessment for efficient development workflows

Workflow for scanning of documents, collecting some meta information for further usage, enhancing the quality of the documents, reducing the file size of them drastically, extract with the help of OCR tools (Tesseract) some plain text, putting the scanned images and extracted texts into one PDF with some (previously collected) meta information and finally organizing all the files within a simple tree structure onto your file system.