Skill UI

A comprehensive forensic workflow for detecting persistent, deep-seated malware, such as bootkits and advanced rootkits. The analysis covers multiple layers, including boot sectors (MBR/VBR), UEFI firmware modules, and kernel memory forensics. It is essential for investigating sophisticated, nation-state level threats that evade standard anti-malware and EDR solutions.

Provide step-by-step explanations of specific files, functions, or modules, leveraging the understand-explain workflow to map graph context, layer placement, internal structure, and data flow for developers needing deep clarity.

Used for systematic deep-dive repair of broken features or modules. It involves five strict phases: Scope, Trace, Diagnose, Fix, and Verify. Unlike quick bug fixes, this method maps all dependencies, checks logs, and ensures the entire feature works end-to-end before proposing solutions.

PyTorch Lightning is a deep learning framework that organizes PyTorch code to eliminate boilerplate while maintaining flexibility. It automates training workflows, supports multi-GPU/TPU orchestration, and implements best practices for neural network training. Features include LightningModules, Trainers, data pipelines, callbacks, logging (W&B, TensorBoard), and distributed training strategies like DDP and FSDP for scalable training.

This skill analyzes an existing codebase using domain context and architectural decisions to identify architectural friction and "deepening opportunities." It proposes refactored improvements to increase module depth, enhancing testability, improving maintainer locality, and making the codebase more navigable for AI tools. It focuses on transforming shallow modules into robust, deeply leveraged components.

A comprehensive guide and shared vocabulary for designing and structuring complex software modules. Use this when you need to refine an existing module's interface, identify opportunities for deepening its capabilities, determine optimal internal seams, or improve code testability and AI-navigability. It establishes clear principles for Module, Interface, Depth, and Seam.

This critical protocol is the ultimate measure for dealing with deeply corrupted, unmaintainable, or structurally rotten code modules. Instead of risky patching, it mandates a controlled, multi-phase process to completely delete the target and rebuild it from scratch. It ensures precise identification of all public interfaces, implicit contracts, and working behaviors (the Preservation List) before any removal occurs, guaranteeing the new implementation matches the original functionality while resolving deep architectural debt.

This skill provides comprehensive pull request (PR) code reviews that go beyond simple syntax checks. It aggressively surfaces deep-rooted decay risks, architectural design smells, and maintainability issues. Findings are reported using a structured Symptom → Source → Consequence → Remedy framework, drawing insights from classic engineering principles. Ideal for reviewing complex or crucial code modules.

This skill facilitates a structured, multi-session brand identity interview across eight key modules including purpose, positioning, and audience. It employs techniques like laddering and the 5 Whys to extract deep insights, persisting data to disk for resumption. The output is a comprehensive master brandbook used to brief designers and writers, making implicit founder knowledge explicit for new or repositioned brands.

A comprehensive tool for producing highly structured briefs on statutes and legislative Acts. Utilizing the MAPS and RULES framework, it maps the entire statutory architecture, extracts operative provisions as rule-modules, and optionally applies the law to specific scenarios. Ideal for deep legal analysis, compliance review, and understanding complex legal texts.

A comprehensive guide and shared vocabulary for designing and structuring complex software modules. Use this when you need to refine an existing module's interface, identify opportunities for deepening its capabilities, determine optimal internal seams, or improve code testability and AI-navigability. It establishes clear principles for Module, Interface, Depth, and Seam.

This critical protocol is the ultimate measure for dealing with deeply corrupted, unmaintainable, or structurally rotten code modules. Instead of risky patching, it mandates a controlled, multi-phase process to completely delete the target and rebuild it from scratch. It ensures precise identification of all public interfaces, implicit contracts, and working behaviors (the Preservation List) before any removal occurs, guaranteeing the new implementation matches the original functionality while resolving deep architectural debt.