Skill UI

A tool designed for persistent context management within AI coding sessions. Memory Kit solves the problem of context loss that occurs during compaction or session restarts by saving, loading, updating, and sharing critical session state to a dedicated `MEMORY.md` file. Key functions include creating snapshots of goals and decisions, syncing context across team members via Git, and auditing/pruning stale entries, ensuring continuous workflow and knowledge retention.

This skill guides the identification and search for specialized crew members (such as production controllers, costume designers, music directors) in South Asian cinema. It is essential when a question focuses on technical roles rather than just the director or lead actors. By using specific search queries on reliable databases (like IMDb or Wikipedia) after identifying the film, users can efficiently locate detailed production credits.

Generates structured DESIGN.md files that serve as a single source of truth for AI-powered screen generation (Google Stitch). This skill translates complex, anti-generic design directives into precise semantic rules, covering typography, color calibration, motion physics, and layout principles to enforce a premium, high-agency UI/UX standard. It ensures outputs are sophisticated and avoid common AI design clichés.

A deep-dive session designed to stress-test a technical plan against an existing domain model. This process forces the user to resolve ambiguities, sharpen terminology, and validate decisions by cross-referencing code and existing documentation (CONTEXT.md, ADRs). It ensures architectural rigor and completeness before implementation.

This comprehensive playbook details advanced techniques for exploiting Layer 2 and Layer 3 network protocols. It covers attacks such as ARP spoofing, LLMNR/mDNS poisoning, WPAD abuse, DHCPv6 takeover, VLAN hopping, and STP manipulation. Designed for penetration testers, it facilitates MitM positioning, credential harvesting (NTLM relay), and robust network environment exploitation.

A structured founder interview designed to gather the canonical, comprehensive data for a company, including financials, team structure, business metrics, and strategic risks. It generates a single, authoritative `company-context.md` file, serving as the single source of truth for all subsequent AI agents and strategic decision-making processes. Essential for initial setup or after major company life events like funding rounds or pivots.

This tool performs a rigorous, simulated Quality Management System (QMS) audit based on ISO 13485 standards for medical devices. It forces interrogation on critical areas, including Design History Files (DHF), CAPA effectiveness, process validation, risk management (ISO 14971), and post-market surveillance (MDR/FDA QSR). Use it before major audits, commercial launches, or regulatory submissions to identify compliance gaps.

This skill facilitates a rigorous, documentation-anchored design review session. It challenges a proposed plan by cross-referencing it against the project's established domain glossary (CONTEXT.md), historical architectural decisions (ADRs), and the current codebase. It forces the user to resolve ambiguities, define precise terminology, and validate design trade-offs using concrete scenarios, ensuring all decisions are captured and documented inline.

This is a mandatory, one-time setup skill designed to interview users interactively to build a personalized knowledge base for advanced email triage. Using a structured, discipline-driven interview process, the skill collects data on email patterns, business context, and priorities, generating 7 critical structured files (e.g., email-taxonomy.md, rate-card.md). This knowledge base powers the companion 'inbox-triage' skill. Run this before initial use or whenever core business processes change significantly.

This technical skill is designed to verify the compatibility of the Codex CLI with skills compiled from MDA source. Loading this skill confirms that the CLI loader successfully parses the SKILL.md format, adhering to the agentskills.io v1 envelope subset. It is primarily used for testing build pipelines, metadata integrity, and ensuring robust compatibility between MDA compilation and runtime ingestion.

This skill captures and persists critical user decisions, project constraints, and architectural choices across multiple sessions and agents. It saves this context into a structured memory database (`mdbase`), ensuring that future development steps or agents can retrieve the original intent without re-deriving it from scratch. Ideal for documenting project rules, tech stacks, and design rationale.

Converts complex, long-form markdown (like RFCs, specs, or reports) into a single, polished, and lightly interactive HTML file. It features a sticky Table of Contents, search functionality, advanced code-copy buttons, and integrates with design systems for professional branding, all without needing a build step or framework runtime.