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概要と使いどころ
Turn hand-made first-50 traction into self-reinforcing acquisition loops, so the next 5,000 users come from usage, not founder hours. Use when growth stalls the moment the user stops pushing, every signup traces back to a DM or one launch spike, or they're reaching for "more channels" when the real gap is that using the product creates no new users.
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。
Create platform-native content that resonates with each community's culture. Use when adapting technical content for WeChat, Hacker News, Reddit, Medium, Twitter/X, Dev.to, or LinkedIn. Transforms generic writing into content that feels written BY that community, not AT them.
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。
This skill should be used when the user asks to "write a branching story", "interactive fiction", "choose your own adventure", "plan the branches", "choice graph", "add a choice", "gamebook", "Twine", "Ink", "draft a branch", "where the branches rejoin", "add an ending", "unreachable chapter", "path continuity", "state-differs-by-path", or wants to plan, draft, or revise a story project whose chapters carry `choices`. NOT for turning a finished linear book into an interactive edition in Ink or Twine (use adaptation).
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。
Audits GitHub Actions workflows for security vulnerabilities in AI agent integrations including Claude Code Action, Gemini CLI, OpenAI Codex, and GitHub AI Inference. Detects attack vectors where attacker-controlled input reaches. AI agents running in CI/CD pipelines.
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。
Alumni and re-hire register: former role, last working day, re-hire eligibility, current employer and re-engagement date, as CSV, SQL, JSON Schema or Notion on request. Use for alumni outreach.
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。
Audit a live page for accessibility issues, locate each WCAG violation precisely, and return a selector-grounded fix worklist without editing.
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 and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
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。
After you give a substantive answer or draft that the user may act on — advice or recommendations, drafted artifacts such as goals, plans, pitches, proposals, or emails, estimates or projections, analysis or interpretation of data, factual claims they may rely on, or a multi-step argument — invoke this skill BEFORE finalizing your reply and then, if it applies, append 2-3 short follow-up questions, each tied to something specific in what you just produced, that help the user check key facts, probe the reasoning or assumptions, and notice missing context. Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.
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。
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.
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。
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.
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。
临考复习教练 / Exam cram coach. 学生给一个课程资料文件夹（课件 PDF/PPTX/DOCX/笔记/作业/答案/真题/往年卷），它按章节讲解并标出处、把讲义和题目里的图裁出来展示、只用资料里的题考试判分、记错题和笔记、按天排复习计划、做小抄，并标明每句话是否来自资料。触发词：期末、期中、考试、备考、复习、突击、刷题、真题、作业讲解、错题本、划重点、小抄、复习计划、考研、考证、课件讲解、讲义。Use when a student wants to prepare for a final, midterm or any exam from their own course files: teach chapter by chapter with page citations and the figures cropped from the materials, quiz only from the homework and past papers, keep progress, mistakes and notes across chats, plan the remaining days, build a cheat sheet, and label what comes from the materials. Triggers: exam prep, cram, revise, study for the test, lecture slides, homework solutions, past papers, practice questions, quiz me, mistake log, cheat sheet, study plan, study guide, flashcards.
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。
Vendor privacy risk tiering methodology for processor management. Covers scoring factors including data volume, sensitivity, transfer locations, certifications, breach history, and control maturity with weighted risk calculation and tier assignment.
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。
Guides the periodic DPIA review lifecycle including trigger identification for regulatory changes, new data categories, technology changes, and breach incidents. Covers version control, stakeholder sign-off procedures, and DPIA register management per Art. 35(11). Keywords: DPIA review, PIA update, review cadence, version control, Art. 35(11), periodic review, trigger events, stakeholder sign-off.
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。
Comprehensive PET selection guide covering differential privacy, homomorphic encryption, secure multi-party computation, federated learning, zero-knowledge proofs, and trusted execution environments. Includes use-case matching matrix, performance comparison, and GDPR alignment assessment for each technology.
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。
Manages HIPAA Business Associate Agreements under 45 CFR §164.502(e) and §164.504(e). Covers required BAA provisions, business associate vs subcontractor obligations, breach notification chain, downstream BA requirements, and termination remedies. Keywords: BAA, business associate, subcontractor, HIPAA compliance, PHI disclosure, termination.
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。
Guides determination of the correct lawful basis under GDPR Article 6(1)(a)-(f) for each processing activity. Includes decision tree logic for consent vs legitimate interest vs contract necessity. Activate when evaluating legal grounds for processing or reviewing lawful basis selections. Keywords: lawful basis, Article 6, consent, legitimate interest, legal obligation, contract.
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。
Addresses HIPAA compliance for mobile health (mHealth) applications, wearable devices, and remote patient monitoring. Covers OCR guidance on mobile device PHI, FDA-regulated mobile medical applications, FTC Health Breach Notification Rule for non-HIPAA apps, BYOD policies, and encryption requirements for ePHI on mobile platforms. Keywords: mHealth, mobile health, HIPAA mobile, wearable, remote monitoring, BYOD, mobile device management, app privacy.
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。
Nigeria Data Protection Regulation (NDPR) and Nigeria Data Protection Act (NDPA) 2023 compliance. Covers lawful basis for processing, data subject rights, cross-border transfer mechanisms, Data Protection Compliance Organisation (DPCO) registration, mandatory DPIA filing, and breach notification. Keywords: NDPR, NDPA, Nigeria, NITDA, DPCO, Africa data protection, cross-border transfer.
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。
Implements data lineage tracking for privacy compliance including origin tracking, transformation logging, access auditing, deletion verification, and cross-system lineage graphs. Covers source-to-sink mapping, GDPR Art. 30 RoPA integration, automated lineage discovery, and breach impact scoping. Keywords: data lineage, data provenance, data flow mapping, transformation logging, deletion verification.
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。
Guides implementation of the GDPR accountability principle under Articles 5(2) and 24, including documentation requirements for policies, DPIAs, RoPA, training records, and breach logs. Activate when establishing or reviewing accountability measures, preparing evidence portfolios, or demonstrating compliance to supervisory authorities. Keywords: accountability, Article 5(2), Article 24, documentation, compliance evidence, governance.
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。
Guides managing conflicting privacy requirements across jurisdictions. Covers data localisation vs transfer freedom, consent standards variation, age thresholds, breach timelines, and resolution frameworks for incompatible obligations. Keywords: conflicting laws, data localisation, consent variation, age thresholds, resolution framework.
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。
Break a work-items.md file (produced by /plan-work-items) into independently-grabbable GitHub issues, one per slice, in each slice's target repo. Use when you want to turn a work-items file into GitHub issues, publish work items as issue tickets, or create implementation tickets that can be worked on and tracked on GitHub. Does not produce the work-items file itself — use plan-work-items to break a plan into work items first. Does not review code or post pull request comments — use post-code-review-to-pr for that.
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。
Designs the contract for an API change inside one codebase — a component's props, a function surface, URL or query parameters, an event payload, or a module boundary — through a discovery pass, an options document with one recommendation, a question round, and an adversarial validation round, with every element of the contract justified from one stated goal. Use when you want to design, shape, decide, or nail down an interface, contract, signature, or API change for a capability you can already describe, sized for roughly one pull request. Produces a design document and changes no code. Does not specify what a feature should do — use plan-a-feature. Does not plan delivery or sequencing — use plan-implementation. Does not assess the architecture of existing code — use architectural-analysis. Does not write the code — use tdd. Does not restructure existing code — use refactor. Runs its rounds without pausing for review; to review each round as it lands, use pairing.
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。
Builds a feature implementation plan from an existing feature specification (or equivalent context) through a facilitated team conversation. Use when the user wants to plan how to implement, build, deliver, or ship a feature that has already been specified. Does not specify what the feature should do — use plan-a-feature first. Does not design the contract for an interface — use design-an-api. Does not refine or stress-test an already-written plan — use iterative-plan-review. Runs its resolution rounds to completion and holds its questions until after they finish; to review each round as it lands, use pairing.
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。