Results for “course”

Expert in designing engaging learning experiences - completion optimization, multimedia learning, interactivity, gamification, and retention strategies. Covers the science of how people learn and practical techniques to make courses that students actually finish. Use when "learning experience, course engagement, completion rate, make learning fun, gamification, interactive course, learning design, " mentioned.

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Expert in course platform selection and implementation - comparing Teachable, Kajabi, Thinkific, and custom solutions. Covers LMS selection criteria, platform migrations, tech stack decisions, and building vs buying. Use when "course platform, lms, teachable, kajabi, thinkific, course hosting, learning management system, which platform, " mentioned.

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Rebuild or update the course overview video (about 98 seconds) for this course in videos/overview. Use when running /overview-video, or when asked to refresh the course overview video, add a chapter or feature to it, retake its dark-mode app screenshots, change its copy or timing, add music, or render a new MP4.

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Generate a self-contained HTML changelog report showing recent documentation changes with interactive course generation buttons. Use this skill when the user asks for a docs changelog, documentation report, what changed recently, recent doc updates as a report, or runs `/docs --report`. Discovers changes via git history, categorizes them, summarizes what's new, and produces a stunning Obsidian & Amber themed HTML report where each entry has a "Create Course" button that copies the course command to clipboard.

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Use when a task needs the judgment of a Postsecondary Computer Science Professor — diagnosing why a course's DFW (D/F/withdraw) rate spiked, redesigning an intro programming course's assessment structure, staffing TAs and grading load for a large course, deciding what to prioritize pre-tenure, running an academic-integrity (MOSS similarity) investigation, or mapping a curriculum change against ABET student outcomes.

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Cross-cultural communication frameworks for understanding discourse patterns across cultures

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Builds a DRAFT course outline from a training need and audience: learning objectives with an observable verb, condition and standard, modules in a stated order with a duration basis and sources, activities and an assessment plan aligned objective by objective, and a coverage table showing what each objective still lacks. Never sets a pass mark, declares learners competent or invents content. Use when the user asks to "build a course outline", "design a training programme for", "turn this need into modules and objectives", "draft the curriculum for this workshop" or "what should this training cover". Do not use for quiz items from finished content, use training-quiz-builder instead; for needs from surveys and manager notes, use training-needs-synthesis; for a new starter's first weeks, use onboarding-plan-builder. Drafts for human review; never approves, authorises or signs off.

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Synthesises training survey responses and manager notes into a DRAFT training needs report by role: coded needs with record counts per role (n of N), the evidence type behind each count, anonymised quotes cited to record codes, disagreements between what staff report and what managers observe, gaps where a role is under-represented or a required skill has no evidence, and follow-up questions to settle before any course is designed. Never rates an individual, ranks a team or turns a count into a competence verdict. Use when the user asks to "analyse this training survey", "what training do our teams need", "summarise the manager feedback on skills gaps", "build a training needs analysis by role" or "which roles have the biggest skill gaps". Do not use for turning an agreed need into a course, use course-outline-builder instead; for exit interviews, use exit-interview-synthesis. Drafts for human review; never approves, authorises or signs off.

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Refresh a safe, concise map of this GCI World 2026 workspace before deeper course, assignment, or dataset work.

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Course creator — Curriculum design, video production, LMS setup, pricing, launch strategy

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Find relevant lessons in AI Engineering from Scratch from a topic, question, or bug. Get a short selection of lessons, necessary prerequisites, and the next learning command, with dedicated routes for specialized subjects.

• Finding lessons on a topic you want to learn
• Locating lessons that explain a bug's underlying cause
• Choosing what to study next based on your progress

Build a new classroom course through an agreed page plan, teacher and learner personas, ordered page generation, and final checks. It defines when pages and narration audio are complete and how to handle generation failures.

• Building a new classroom course from scratch
• Setting teacher and learner personas before generating pages
• Checking saved pages and narration audio for completeness

Use a teacher's recordings or lecture materials to identify evidenced teaching habits, including phrasing, examples, pacing, and visual presentation. Apply those habits to a course on a requested topic, keeping its subject facts separate from the source lesson.

• Creating a new lesson with a familiar teaching style
• Analyzing recurring phrases and explanation patterns
• Studying how speech and on-screen visuals work together

Design hands-on workshops with short explanations, immediate exercises, and quick self-checks. Use brief dialogue between a teacher and an assistant to guide practice, then finish with a small project that combines what learners have tried.

• Create a workshop built around hands-on practice
• Turn long explanations into short briefs and exercises
• Write guiding dialogue for a teacher and assistant

Design vocational training around a real work task, from preparation and equipment checks to operation, verification, and handover. Build interactive practice with tools, ordered steps, consequences for mistakes, and checkpoints where learners decide whether to proceed, recheck, or stop.

• Designing hands-on vocational training
• Practicing equipment checks and operating steps
• Adding proceed-or-stop decisions for unsafe conditions

Work with Google Classroom through gog to inspect courses, assignments, student submissions, and class rosters. It guides agents through the available commands and account checks needed to handle classroom information and operations.

• Checking courses and assignments
• Reviewing student submissions
• Checking student and teacher rosters

Use this skill when the user asks about Ni Haisha / 倪海厦 TCM course material, especially Shang Han Lun / 伤寒论, Jingui / 金匮要略, Zhongjing Xinfa / 仲景心法, clinical cases / 临床案例 / 倪师医案, Bagang Bianzheng / 八纲辨证, Fuyang Forum / 扶阳论坛, Yijinjing / 易筋经, Liang Dong dialogue / 梁冬对话倪师, Stanford lecture / 斯坦福大学演讲, Tianji / 天纪 / 易经 / 阳宅 / 紫微斗数, Huangdi Neijing / 黄帝内经, Shennong Bencao / 神农本草, acupuncture / 针灸, meridians, acupoints, acupuncture depth safety / 危险进针深度 / 气胸风险, six-channel pattern identification, symptom-to-formula routing, formula comparison, lesson review, board/PPT screenshot evidence, or course-derived study notes. This skill is for educational distillation and study support only, not medical diagnosis, prescriptions, dosage, individualized treatment, or self-administered acupuncture.

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Turn student course evaluations (free-text + numeric) into an actionable teaching-improvement plan — the teaching analogue of /respond-to-referees. Clusters comments into themes, separates signal from noise, classifies each theme Keep / Change / Investigate / Out-of-scope, and drafts concrete changes mapped to the syllabus and slide decks. Use when user says "respond to my evals", "what do these course evaluations tell me", "turn my teaching feedback into a plan", or after a semester's evals arrive.

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Analyzes time-series and longitudinal RNA-seq for differential expression and trajectory structure. Covers DESeq2 LRT with reduced models, time as factor vs continuous vs natural splines, maSigPro (Nueda 2014 for RNA-seq), ImpulseDE2 with explicit impulse-model failure modes, DREAM for repeated measures via linear mixed models, pseudoreplication avoidance, conditional vs marginal modeling, and trajectory clustering with DPGP, Mfuzz (with Schwämmle 2010 fuzzifier estimation), and splines+k-means. Use when modeling time-course or longitudinal expression, choosing factor vs spline, handling repeated measures from the same subject, avoiding pseudoreplication, clustering temporal trajectories, or selecting between dedicated time-course tools and pairwise+LRT.

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Designing lead magnets that earn the email. The discipline of building gated content (ebooks, templates, checklists, swipe files, mini-courses, free tools) that delivers genuine standalone value while qualifying the lead and warming them for what comes next. Honest about thin-bait (overpromises, underdelivers), kitchen-sink-resource (everything, helps with nothing), and earned-value-magnet (delivers standalone value while qualifying the lead). Triggers on lead magnet, gated content, opt-in offer, ebook, checklist, template, swipe file, mini-course, free tool, content upgrade, freebie, opt-in, list-building offer. Also triggers when an audience is being asked for an email and the offer attached to that ask needs design discipline, when previous lead magnets converted but did not produce qualified leads, or when a lead magnet is being scoped for the first time.

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Generate tiered sentence frames for academic tasks that scaffold language production across proficiency levels. Use when EAL students need structured language support for classroom discourse.

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Drive the real Course Video Manager web app in a browser and capture proof of what it did. Use to verify a change before opening a PR, to reproduce a reported UI bug, to see what a page actually renders, or to capture a screenshot of app behaviour. Runs on a per-run, writable clone of a local copy of Matt's data by default — click anything that mutates; production is never written to.

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Generate or update documentation for the AI Hero API by reading the source code at ~/repos/ai/course-builder. Use when user wants to document, update docs for, or understand the AI Hero API endpoints.

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Optimize slow React Router loaders by eliminating redundant DB queries, creating slim query variants, and parallelizing independent fetches. Use proactively when writing or reviewing loader code that calls domain operations services (e.g. CourseOperationsService, VideoOperationsService), or when triaging a slow page load.

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