Skill UI

This guide establishes a comprehensive and rapid development loop for Obsidian plugins. It covers the entire workflow, from setup (cloning templates, symlinking) to advanced features, including running esbuild in watch mode, achieving hot-reloading (via Ctrl+R or automatic methods), deep debugging with Chrome DevTools, and running unit tests with vitest. Essential for developers seeking fast feedback and reliable plugin iteration.

Guidelines for responding to code review feedback with technical rigor: read every comment, restate requirements, verify against the codebase, ask clarifying questions, push back when technically needed, and implement fixes one at a time with testing.

This workflow provides an AI-powered platform for immersive conversation practice. It uses advanced language models (like GPT-4o) and real-time speech APIs to simulate real-life scenarios (e.g., ordering food, navigating). Users receive immediate, detailed feedback on pronunciation (phoneme level), grammar corrections, and vocabulary notes, making it an ideal core module for building language fluency and simulating professional tutoring experiences.

This guide details how to set up the Speak language learning platform integration. It covers installing necessary SDKs (Speak SDK, OpenAI), configuring API keys, and establishing the connection required for sophisticated AI-powered tutoring. Use this when building applications that require real-time speech recognition, pronunciation feedback, and multilingual language support.

Structured manuscript and grant review guidance that walks reviewers through methodology, statistics, reporting compliance, and constructive feedback for rigorous scientific evaluation across disciplines.

Guides developers through receiving and responding to code review feedback: read carefully, restate requirements, verify against the codebase, evaluate correctness, push back with technical reasoning if needed, and implement one verified fix at a time.

Explains when to call the code-reviewer subagent, how to collect SHAs, fill the template, and act on its feedback so every task, feature, or merge meets quality expectations.

Helps product teams structure customer discovery interviews by clarifying goals, segments, constraints, and adaptive methods so each session yields actionable insights instead of confirmation bias or surface-level feedback.

Provides actionable guidance and review checklists for modern clean UI/UX, emphasizing CRAP principles, task-first flows, information architecture, system feedback, consistency, and refined iconography.

This solution guides the implementation of a phishing reporting button within email clients, creating a critical feedback loop for security teams. By integrating with SOAR platforms, reported suspicious emails undergo automated triage, including IOC extraction, sandbox analysis, and threat intelligence checks. The workflow enables rapid classification, automated remediation (e.g., mass retraction, sender blocking), and provides detailed feedback to the user reporter, significantly enhancing overall security posture.

Build a production-ready, AI-powered data collection agent for any public source (job boards, prices, news, etc.). This agent automatically scrapes data, enriches it using free LLMs (like Gemini Flash), and stores the results in databases such as Notion, Sheets, or Supabase. It runs on a free schedule using GitHub Actions and learns from user feedback, making it ideal for continuous data monitoring and tracking.

This skill guides the implementation of a full Cyber Threat Intelligence (CTI) program across the six-phase intelligence lifecycle. It covers defining intelligence requirements (PIRs), building collection pipelines, normalizing data, performing analysis, and managing feedback loops. Ideal for maturing existing CTI teams or establishing foundational security intelligence capabilities.