Skill UI

This tool parses a structured, multi-shot video script (following the ai-video-script format) and automatically generates a time-coded SRT subtitle file. It calculates cumulative timestamps based on the duration of each shot, ensuring accurate subtitle cues that sync with the voiceover content across the entire sequence. Ideal for the post-production stage of short-form video creation.

This skill provides a comprehensive, step-by-step workflow for generating complete Power BI reports from scratch using the pbir CLI. It covers everything from initial model discovery and defining design briefs to visual placement, formatting, filtering, validation, and final publishing in Fabric or Power BI Desktop. It ensures best practices are followed to create robust, professional, and interactive dashboards.

This skill enables the creation of a robust 'harness' system for coding agents within a repository. It addresses the need to prevent repeated AI-generated coding mistakes by implementing durable instructions, guardrails, regression tests, and failure memory. It treats the target repository as the source of truth, ensuring consistency and maintaining high reliability across all automated contributions.

A powerful command-line tool for recording the macOS screen and capturing system audio simultaneously. Unlike QuickTime or standard `screencapture`, this tool captures raw display and system audio directly via ScreenCaptureKit, eliminating the need for complex virtual audio drivers (like BlackHole) or elevated permissions. It is designed for scripted content creation, automated demos, and complex recording scenarios where system audio is required via the CLI.

A comprehensive guide and playbook for managing feature flags across services or teams. It covers flag taxonomy (Release, Experiment, Ops, Permission), naming conventions, safe rollout strategies, creation checklists, and cleanup policies to prevent technical debt. Ideal for standardizing feature flag practices and governance.

This skill automates the creation of high-quality, structured pull request descriptions. By analyzing git diffs, commit lists, or raw changes, it generates comprehensive sections covering the summary, motivation, specific changes, detailed testing procedures, and crucial reviewer guidance. Use it to ensure every code change is fully documented for effective peer review.