Skill UI

A comprehensive coach designed to prepare individuals for top-tier strategy consulting interviews (MBB, Big Four). It covers structured problem-solving, mastering core consulting frameworks (MECE, Hypothesis-driven thinking), building compelling narratives, and handling specific case types (Profitability, M&A, Market Sizing). Ideal for candidates aiming to master the entire consulting recruiting funnel, from behavioral interviews to complex case analysis.

A comprehensive system designed to master all major interview formats globally. It simulates mock interviews, coaching behavioral skills (STAR method), technical problem-solving, and consulting case studies. The coach provides culturally calibrated advice for specific contexts, including Chinese civil service exams, state-owned enterprise interviews, and major tech company assessments, ensuring users are prepared for any professional challenge.

Execute comprehensive, asynchronous transcription workflows using AssemblyAI. This tool handles file upload, queues jobs, and provides advanced audio intelligence features. Capabilities include speaker diarization, sentiment analysis, named entity recognition (NER), topic categorization (IAB), content safety moderation, and sensitive PII redaction. Ideal for processing meeting recordings, interviews, and large volumes of spoken content.

This skill provides a comprehensive, multi-phase guide for authors to draft a Specification Enhancement Proposal (SEP) adhering to rigorous governance standards. It walks users through prerequisites, initial vetting (Gate), detailed interviews (e.g., breaking changes, security), and technical research, ensuring the proposed change is viable and community-vetted before formal submission.

This skill guides developers through creating a comprehensive refactoring plan and serving as a Request for Comments (RFC). It orchestrates detailed interviews, codebase analysis, and scope definition. It ensures the refactor is broken down into tiny, safe, incremental commits, culminating in a structured GitHub issue that serves as a definitive architectural and technical decision document.

This meta-skill orchestrates complex, multi-step job search workflows, moving beyond simple advice. It is designed for concrete tasks such as tailoring resumes to specific job descriptions (JDs), building complete application packs, preparing for named interviews, comparing multiple job roles, or maintaining an organized application tracker. It focuses on producing reviewable artifacts and never performs automatic applications.

This skill manages and maintains your personal context portfolio, a structured set of markdown files detailing your identity, professional roles, team information, and system configurations. It guides users through first-time setup interviews, detects missing or incomplete information (e.g., TODO placeholders), and facilitates targeted updates when your professional context changes.

A comprehensive framework for structuring user interviews, customer discovery, or Jobs-to-be-Done (JTBD) research. This guide provides structured steps for screener creation, deep behavioral exploration (focusing on past actions, not future predictions), and systematic synthesis/pattern detection, ensuring the gathering of genuine, actionable insights.

This skill synthesizes user signals gathered from diverse sources—such as interviews, support tickets, NPS verbatims, app reviews, and sales calls—into a single, weighted, and comprehensive insight brief. It moves beyond surface-level feature requests to surface the core underlying user needs, identifies contradictions (divergence), and assigns confidence ratings based on source diversity and weight. Ideal for product managers and UX researchers needing to reconcile complex, mixed data sets.

Generates a comprehensive and actionable UX research plan for any product feature or question. This skill covers the entire research lifecycle, including defining objectives, selecting methodology (e.g., usability testing, interviews), creating participant screeners, writing discussion guides, and structuring a synthesis framework. Ideal for product managers and UX researchers needing a structured approach to validate assumptions and drive design decisions.

This guide provides comprehensive standards for achieving auditability and transparency in Computer-Supported Cooperative Work (CSCW) research. It teaches researchers how to document non-shareable evidence, such as field interviews, log traces, and system deployments, by focusing on detailed analysis trails, decision logs, and rigorous process documentation, thus strengthening academic rigor.

This guide helps authors prepare for high-level theoretical journal submissions, focusing on the specific requirements of single-anonymous peer review. It details appropriate article types (Article, Miscellanea, ET Interviews), and provides a comprehensive checklist to war-game potential referee objections regarding assumptions, proof gaps, convergence rates, and novelty, significantly improving submission quality.