Skill UI

This skill processes raw, unstructured materials (e.g., conversations, reports, controversies) into highly structured, reusable casebook entries. It focuses on identifying core facts, defining mechanism chains, and mapping responsibility links while ensuring rigorous data anonymization. It is designed for deep knowledge management and pattern recognition, helping users build a reliable, reusable knowledge base for future professional analysis, rather than generating immediate advice.

This skill systematically defines all necessary variants, states, and properties for a Figma component before development. It ensures comprehensive coverage of all states (e.g., Hover, Disabled, Loading) and properties (e.g., Size, Type), generating a robust variant matrix that prevents critical design gaps and streamlines the entire component building process in Figma.

This skill outlines a systematic, multi-phase workflow for diagnosing hard bugs and performance regressions in complex codebases. It emphasizes the critical necessity of building a tight, deterministic feedback loop (Phase 1) before moving to hypothesis generation. The process guides users through reproducing the failure, minimizing the scope of the issue, and forming actionable, ranked hypotheses.

This skill implements the LLM Council concept, enabling multiple open-weight language models to collaborate on complex queries. The process follows a three-stage deliberation: 1) Parallel independent responses from selected models; 2) Peer-to-peer ranking of the responses; and 3) Final synthesis by a designated Chairman LLM. Powered by Fireworks AI, it ensures deep, multi-faceted analysis and consensus building for high-stakes decision support.

Builds comprehensive identity governance and lifecycle management processes. Automates the entire employee journey (Joiner, Mover, Leaver) from the authoritative HR source of truth. This process handles role-based access provisioning, access request workflows, periodic recertification, and remediation of orphaned accounts, ensuring continuous compliance with standards like SOX and GDPR.

This skill details the process of building and maintaining a comprehensive anti-phishing training program. It covers establishing baseline susceptibility assessments, deploying regular, progressive simulations, and providing interactive, role-based learning modules (using platforms like KnowBe4 or Proofpoint). The focus is on measuring and improving the human layer of defense against social engineering and sophisticated phishing attempts, thereby fostering a continuous security culture.

Plaso (log2timeline) is an open-source engine used to generate forensic super-timelines. This skill guides the process of normalizing hundreds of diverse artifact types—including MACB times, registry keys, EVTX logs, and browser history—into a single, cohesive chronological view. The workflow covers extraction, filtering, and importing the timeline into Timesketch for collaborative analysis, which is crucial for incident response, correlating complex activity chains, and detecting anti-forensic techniques like timestomping.

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 comprehensive skill acts as a virtual Chief of Staff, guiding founders through a rigorous 12-phase interview process. It systematically gathers and structures every facet of a business—from foundation and strategy to legal and governance—into a compliant Open Knowledge Format (OKF) bundle. Ideal for creating comprehensive, machine-readable company documentation, internal wikis, or knowledge bases for AI agents.

A comprehensive utility for building reusable, command-line scripts and utilities to interact with the Hugging Face API. It enables complex data workflows by allowing users to chain, pipe, and process data fetched from models, datasets, and various endpoints. Ideal for automation, enrichment, and advanced data pipelines.

A comprehensive guide for developers building AI demos and GPU compute tasks on Hugging Face Spaces using ZeroGPU hardware. It covers best practices for writing and reviewing code that utilizes the `@spaces.GPU` decorator, managing runtime duration and quota, and understanding the specific CUDA availability model and process isolation rules required for reliable ML deployment.

Generate comprehensive, ready-to-use CI/CD pipeline configurations for running automated API tests using Newman. This skill provides templates for major platforms like GitHub Actions, GitLab CI, Jenkins, and Azure DevOps. It ensures seamless integration of Postman collections into automated build processes, including setting up environment variables, running tests, and publishing detailed JUnit and HTML reports.