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概要と使いどころ
MATLAB R2026a workflow for signal processing, DSP, image processing, computer vision, lidar, medical imaging, deep learning, and AI-assisted reproducible experiments. Use for filters, spectrograms, wavelets, object detection, segmentation, classification, training, inference, and generated figures.
日本語の概要は準備中です。原文の説明を表示しています。
Reflect reusable learnings into a private Agent Skills repository with scoped safety gates and same-run private commit/push. Not for ~/.copilot personal assets, VS Code User Data assets, or workspace/repository assets. Use when: skill retro, private skill authoring, skill repository fix, create or update SKILL.md.
日本語の概要は準備中です。原文の説明を表示しています。
"Apply the Uppsala Internationalization Model to analyze gradual foreign market entry based on psychic distance and experiential learning. Use this skill when the user needs to plan a staged internationalization sequence, understand why firms enter culturally similar markets first, or evaluate whether a firm's international expansion follows the establishment chain from export to subsidiary.".
日本語の概要は準備中です。原文の説明を表示しています。
"Apply flow theory to diagnose optimal experience conditions and design environments that balance challenge and skill for sustained engagement. Use this skill when the user needs to explain why users disengage from tasks, optimize task difficulty for peak performance, design learning progressions or gamification systems, or when they ask 'why do people lose focus', 'how to design for engagement', or 'what conditions produce peak performance'.".
日本語の概要は準備中です。原文の説明を表示しています。
"Apply Smith and Lewis's paradox theory to identify and manage organizational tensions across performing, organizing, belonging, and learning dimensions. Use this skill when the user needs to diagnose persistent either/or tensions, design dynamic equilibrium strategies that embrace both poles, or when they ask 'why does solving this problem make it worse', 'how do we pursue exploration AND exploitation simultaneously', or 'why do our strategic tensions keep recurring despite resolution attempts'.".
日本語の概要は準備中です。原文の説明を表示しています。
"Apply the Balanced Scorecard (BSC) framework to translate strategy into measurable objectives across Financial, Customer, Internal Process, and Learning & Growth perspectives. Use this skill when the user needs to set strategic KPIs, create a strategy map, align organizational goals, or connect daily operations to strategic vision — even if they say 'how do we measure strategy execution' or 'our KPIs feel disconnected'.".
日本語の概要は準備中です。原文の説明を表示しています。
"Design multi-objective e-commerce product ranking combining relevance, conversion, and business metrics. Use this skill when the user needs to build a product ranking system beyond text relevance, balance relevance with commercial objectives, or implement learning-to-rank — even if they say 'product sorting', 'search result ranking', or 'how to rank products'.".
日本語の概要は準備中です。原文の説明を表示しています。
Use when exploring, continuing, or accepting a deep-learning or computer-science research idea. Converts claims into pilot-first experiment matrices covering diagnostics, failure analysis, authorized execution, evaluation, and paper-story viability.
日本語の概要は準備中です。原文の説明を表示しています。
Use when planning a source-grounded method overview, architecture, pipeline, system/data-flow, mechanism, or agent-workflow figure for a CS or deep-learning paper. Produces an editable figure brief before image generation or manual redrawing; not for plots, tables, or general prose.
日本語の概要は準備中です。原文の説明を表示しています。
Assess organizational training needs using ADDIE methodology and Kirkpatrick's 4-Level evaluation framework. Maps performance gaps to learning objectives using Bloom's taxonomy. Use when planning L&D budgets, designing training programs, or evaluating training effectiveness.
日本語の概要は準備中です。原文の説明を表示しています。
Simulate supply chain and adversarial machine learning attacks by injecting poisoned data or targeted backdoors into training and fine-tuning datasets. Use this skill when assessing the integrity controls of MLOps pipelines or evaluating the resilience of AI models against highly targeted, stealthy manipulation intended to alter model behavior on specific triggers.
日本語の概要は準備中です。原文の説明を表示しています。
Execute and analyze AI Data Poisoning attacks. By subtly injecting malicious or targeted misinformation into an LLM's training or fine-tuning dataset, an attacker can covertly manipulate the model's future outputs, implant backdoors, or enforce biases without altering the model architecture.
日本語の概要は準備中です。原文の説明を表示しています。
Identify and simulate Data Poisoning attacks aimed at degrading or skewing an AI model's accuracy. This skill focuses on Adversarial Machine Learning concepts where attackers inject malicious or mislabelled data points into training or fine-tuning datasets (e.g., feedback loops) to bias the AI.
日本語の概要は準備中です。原文の説明を表示しています。
Frappe LMS customization guidance for courses, batches, lessons, quizzes, assessments, enrollment, progress, certificates, portals, and learning workflows. Use when work touches Frappe LMS or education/training flows.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to be taught an Anthropic product or feature - "teach me Claude Code", "learn Cowork", "academy lesson", "train me on MCP or the Claude API", "quiz me", "next lesson" - or asks for structured learning rather than a one-off answer. Covers Claude Code, Claude.ai, Cowork, Tag, Platform/API, and AI Fluency. Do NOT use for auditing how the user already works (use academy-review) or for mid-task help where the user just wants their task done.
日本語の概要は準備中です。原文の説明を表示しています。
Master orchestrator for B2B SaaS content creation and the editorial production system behind it. Use this skill to produce blog articles, whitepapers, case studies, video scripts, newsletters and ghostwritten thought leadership, to develop content strategy, and to run the publishing line itself — content briefs, editorial calendars and production capacity, review and approval workflow, subject-matter-expert access, the style guide, an AI-drafting policy, and a content inventory with owners. Also triggers on: blog, article, case study, whitepaper, newsletter, video script, ghostwriting, content calendar, editorial, thought leadership, content strategy, content brief, content operations, content ops, editorial workflow, managing editor, who reviews this, our content pipeline is stuck, content is stuck in review, content audit, content inventory, content governance, style guide, house style, SME interview, expert interview, freelance writers, AI content policy, how much content can we actually produce. Also owns the customer academy and customer education: online courses, onboarding curriculum, tutorials, certification programs, digital credentials and badges, exam and pass-mark design, course freshness when the product UI changes, and whether the academy should sit behind a login. Triggers on: customer academy, customer education, online course, course library, learning path, curriculum, tutorial, certification program, certified users, digital badge, Open Badges, recertification, exam, pass mark, LMS, Skilljar, our tutorial shows the old UI, our course is out of date, should the academy be gated, do certified customers renew better.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a task needs the judgment of a Career/Technical Education (CTE) Secondary School Teacher — deciding whether a student is authorized to run a piece of shop equipment, diagnosing a Perkins V industry-credential attainment gap, placing a student into a work-based learning slot, resolving an articulation-credit dispute with a partner college, or triaging a CTSO competition-prep versus baseline-instruction time conflict.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a task needs the judgment of a Career/Technical Education Teacher, Postsecondary — defending a shrinking trade or health-science program against a cutback decision, backward-mapping a shop or lab curriculum to an industry credential's exam blueprint, resolving a competency-based grading dispute where a passing average hides a failed safety check-off, or setting the terms of an advisory-committee review or work-based-learning placement.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a task needs the judgment of a Biology Professor at a research university — writing or defending an NIH/NSF grant budget, deciding authorship order on a paper, navigating an IACUC or biosafety protocol, mentoring a PhD student through a stalled project, or converting a course when active-learning data doesn't match student pushback.
日本語の概要は準備中です。原文の説明を表示しています。
Teach a topic, video, article, codebase change, spec, or transcript until the user demonstrably understands it, using staged instruction, a running checklist doc, and quizzes. Use whenever the user says "teach me", "explain this in detail", "help me understand X", "/teach-me", "walk me through this", "I want to learn X", "understand this deeply", or pastes a YouTube URL, article, paper, PR, or spec and asks to understand it rather than summarize it. Also use when the user wants study notes or raw material from a source they are learning. Do NOT use for a quick factual lookup, a summary request, or when the user just wants the answer.
日本語の概要は準備中です。原文の説明を表示しています。
Iteratively study and apply elegant coding patterns. Each iteration - understand the code, research what simple and elegant code looks like, apply learnings, verify with CI. Use as a standalone refactoring pass or when the user asks to make code more elegant, simple, or idiomatic.
日本語の概要は準備中です。原文の説明を表示しています。
Learn effectively from courses and academies: choosing programs, studying actively, and converting courses into skills. Use when investing time/money in structured learning.
日本語の概要は準備中です。原文の説明を表示しています。
Label smarter, not more — pick the most informative examples for annotation to maximize model gains per label.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze learning management and training pathway systems for prerequisite mapping, competency-based progression, adaptive sequencing, and credential stacking.
日本語の概要は準備中です。原文の説明を表示しています。