418건 · 관련도순
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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Use when a NEW product, offer, or course is going to market — beachhead segment selection, launch messaging, channels by phase across pre-launch, launch, and post-launch, milestones, success metrics, and go or no-go criteria. Trigger on 'go-to-market', 'GTM plan', 'product launch plan', 'we are launching a new product', 'beachhead segment', 'how do we launch this course'. Also use when the user has a finished product and no route to the first customers. Not for — the day-by-day execution checklist, see `60-launch-playbook-global`; the ongoing period plan, see `00-marketing-plan-global`; one campaign inside the launch, see `02-campaign-brief-global`; positioning first, see `58-positioning-global`.
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Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.
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Remove the discourse-level (structural) signs of AI writing that survive surface editing: stated lessons and moral-of-the-story closers, tidy single-track arcs, embodied-emotion performance ("chest tightened"), vague allusions instead of named references, unbroken linear structure, and shape convergence across pieces. Grounded in the StoryScope study (Russell et al. 2026): narrative structure alone detects AI text at 93.2% F1, and professional stylistic rewriting moved detection only 1.6 points. Use as the SECOND pass after the humanizer skill (which handles words and phrasing) whenever writing or revising LinkedIn posts, course lessons, blog posts, essays, newsletters, or emails that must read as human. Triggers: "humanize", "de-slop", "AI tells", "make this sound human", "structural pass", "deep humanize".
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Scans HN, Lobsters, Reddit, and tech blogs for community experience reports. Use when gathering practitioner opinions on a technology or approach.
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Stop and check this skill before finishing any reply to a question about how to use Claude or a Claude product — it recommends matching courses, tutorials, and use cases from Claude Academy (academy.claude.com), Anthropic's learning hub. Trigger on: "how do I", "how can I", "getting started with", "what can Claude do", "teach me", "learn to use"; questions about artifacts, projects, skills, plugins, connectors, MCP; requests about rolling Claude out to a team, class, or organization; and any ask for training materials, onboarding content, or learning resources. Use it when the user is learning how to use a feature or product — not when they are mid-task and just want the task done. This skill composes with other skills: after consulting product documentation to answer how a Claude feature works, also check here for a matching course or tutorial — a docs-grounded answer and an Academy recommendation belong together. Only recommend on a strong match; never invent Academy content.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Student weekly assignment planner for Canvas LMS. Shows all due dates, submission status, grades, and peer reviews across all courses. Use when a student says "what's due", "plan my week", "weekly check", or wants to organize their coursework.
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Educator morning course health check for Canvas LMS. Shows submission rates, struggling students, grade distribution, and upcoming deadlines. Trigger phrases include "morning check", "course status", "how are my students", or any start-of-day teaching review.
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Manage significant changes during sprint execution. Use when the user says "correct course" or "propose sprint change"
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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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Assess the impact of a significant change during sprint execution across the PRD, epics, architecture, and UX documents, and produce a sprint change proposal. Use when the user says "correct course" or "propose sprint change"
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Manage significant changes during sprint execution. Use when the user says "correct course" or "propose sprint change"
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Investigate and resolve Course Management Platform CloudWatch alert issues end to end. Use when Codex is asked to inspect a CMP GitHub alert issue, pull dev or production AWS logs, diagnose 5xx responses or failed background work, fix an incident with test-driven development, validate a fix in dev, or deploy and verify an authorized production fix.
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How to reach the platform REST API — where prod and dev live, where the API token is (.env), how to authenticate with curl, and how to fetch the OpenAPI spec listing every endpoint. Use whenever you need to read or edit course/homework/project/registration data, or inspect real prod data while debugging.
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House rules and craft for LaTeX Beamer slide decks (lectures, seminars, talks), drawn from the author's own Overleaf edits and published slide-design guidance. Covers storyboarding, frame titles, slide prose, word and frame budgets, layout without overfull boxes, XeLaTeX fonts and Korean (xeCJK), color, figures and screenshots, Overleaf source hygiene, speaker notes, and a build-and-QA loop with a contact sheet. Use when writing, editing, reviewing, or building a Beamer deck, theme, or storyboard. A course skill supplies course facts and the frame skeleton; this skill supplies the craft. Not for HTML or PowerPoint decks, posters, or papers.
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Router for the /docs command. Look up Claude documentation, ask plain-English questions, generate interactive courses and HTML changelog reports, check freshness, and sync the local cache. Dispatches to the claude-docs, claude-docs-validate, claude-docs-course, and claude-docs-changelog skills.
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将学术论文转换为交互式 HTML 课程 + Markdown 文档 + PPTX 演示文稿，一键生成全部三种输出
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"Habitual Domain (HD) theory by Taiwanese scholar P.L. Yu (游伯龍, 1977) — integrates four domains (potential/actual/reachable/activated), eight general hypotheses, seven-layer decision structure, and nine HD-expansion tools to analyze decision blind spots, break cognitive inertia, and support cross-domain integration. Use for diagnosing why alternatives are invisible, decision paralysis, breaking cognitive frames, or explaining perception gaps between people. Triggers: 『思維框架』『打破盲點』『創新思考』『決策盲區』『跨域整合』『游伯龍』『習慣領域』『HD 理論』『七層決策』『四領域』『八大通性』『P.L. Yu』. Especially for NYCU EMBA HD course, 政大科管所, 中山企管系 decision-analysis/innovation/leadership courses. Taiwan-origin theory cited in J. Optimization Theory, Theory & Decision, Human Systems Management.".
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Learn effectively from courses and academies: choosing programs, studying actively, and converting courses into skills. Use when investing time/money in structured learning.
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Use when a task needs the judgment of an Engineering Teacher, Postsecondary — diagnosing a spike in a gatekeeper course's D/F/W rate, running a capstone design course with an industry sponsor, closing the loop on an ABET student-outcome assessment, or building a tenure/promotion teaching-effectiveness case beyond raw student evaluation scores.
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Use when a task needs the judgment of an Area, Ethnic, or Cultural Studies Professor — designing a joint-appointment course load across two departments, prepping a tenure or mid-tenure review file for interdisciplinary scholarship, deciding whether a course survives an enrollment or political-pressure threat, evaluating community-engaged research for a merit case, or writing a Title VI/FLAS-adjacent grant narrative.
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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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Create interactive AI role-play training activities as self-contained HTML. Use when the user asks to generate a role-play, persona practice, sales simulation, customer conversation drill, compliance scenario, or any learner-vs-AI-character training exercise.
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Manage significant changes during sprint execution. Use when the user says "correct course" or "propose sprint change"
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