AIへの攻撃を想定したテストを設計し、安全指示の回避や機密情報の流出、ツールの不正操作への耐性を調べ、結果と改善方針を整理するスキル。
- AI機能の公開前セキュリティ評価
- 導入候補モデルの安全性比較
- 指示注入や安全指示回避後の再検証
5万 件 ・ 関連度順
概要と使いどころ
AIへの攻撃を想定したテストを設計し、安全指示の回避や機密情報の流出、ツールの不正操作への耐性を調べ、結果と改善方針を整理するスキル。
プロンプト評価、入力容量の配分、検索を使う回答生成の設計、安全性監査、評価基盤、製品企画という六つの観点から、AI開発の進め方を整理する概要スキル。
人が書いたCLAUDE.mdを、AI向けの構造化ラベル形式へ変換します。長い指示のトークン使用量やルール遵守の見直し、AIツール間のルール移行に使えます。
LLMアプリやAIエージェントを対象に、プロンプトインジェクション、個人情報漏えい、モデル改ざんなどへの対策を整理し、本番環境の防御設計を支援するスキル。
AirflowでJavaやKotlinなどのタスクを動かすSDKの開発を支援し、公開APIの境界、JARの構成、通信仕様の更新、テスト手順を案内します。
Apache Airflowへの変更提出に向け、既存PRと送信先の確認、レビューやテスト、最新ブランチへの追従、PR作成の準備、保留作業の記録を案内します。
AIアプリの応答をPhoenixで評価する仕組みを作り、失敗例の分析から評価用データの準備、実験の実行、人の判定との照合まで進めるスキル。
AIの回答から検証可能な主張を抽出し、ウェブの出典と照合します。矛盾や架空の引用の疑いを点検し、人が確認できるリンク付きレポートにまとめるスキル。
個人メールの検索・閲覧から送信・返信、添付ファイルの取得、フォルダや会話単位の整理までをまとめて扱い、メールアカウントの連携や登録も案内するスキル。
AIの技術動向や研究方針、安全対策を、Ilya Sutskeverの公開発言から整理した思考モデルで検討し、結論と身近な例えで説明するスキル。
侵入の記録を攻撃の七段階に当てはめ、攻撃者が進んだ範囲と防御の成否を整理します。検知の抜けを明らかにし、より早い段階で止めるための対策を報告書にまとめます。
Systematic claim-by-claim verification for any content before it ships. Modeled on professional fact-checking desks (The New Yorker, ProPublica, IFCN standards): extract every verifiable claim, check each against live citable sources (never training data), assign a 6-level confidence status, apply corrections, and produce a scored pass/fail report. Includes a data-derived-claims gate for outputs produced FROM the brain or a database: PRODUCER ≠ VERIFIER (re-derive each claim via a different query path) and AFFILIATION ≠ AUTHORSHIP (person→thing claims resolve through typed edges), with delivery hard-blocked on unsupported claims.
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。
When the user wants to write, improve, or build a sequence of B2B cold outreach emails to prospects who haven't asked to hear from them. Use when the user mentions 'cold email,' 'cold outreach,' 'prospecting emails,' 'SDR emails,' 'sales emails,' 'first touch email,' 'follow-up sequence,' or 'email prospecting.' Also use when they share an email draft that sounds too sales-y and needs to be humanized. Distinct from email-sequence (lifecycle/nurture to opted-in subscribers) — this is unsolicited outreach to new prospects. NOT for lifecycle emails, newsletters, or drip campaigns (use email-sequence).
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。
Build with the ChainGPT Web3 AI developer platform. Full API/SDK reference and project scaffolding for: Web3 AI Chatbot & LLM, AI NFT Generator, Smart Contract Generator, Smart Contract Auditor, AI Crypto News, AgenticOS Twitter agents, and Solidity LLM. Use when building blockchain apps, Web3 chatbots, NFT tools, smart contract tools, crypto news feeds, AI agents, or integrating any ChainGPT API. Triggers: chaingpt, web3 ai, nft generator, smart contract audit, crypto news api, agenticos, solidity llm, cgpt, blockchain ai, token analytics.
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。
EU AI Act (Regulation (EU) 2024/1689) compliance advisor — risk classification across all four tiers, all 9 prohibited practices (Art. 5, including the nudification/CSAM prohibition from Dec 2, 2026), all 8 Annex III high-risk use case areas, provider and deployer obligations (Arts. 9–17, 26), GPAI model obligations including the July 2025 Code of Practice (Arts. 51–55), conformity assessment and CE marking (Arts. 43–48), EU AI database registration, Art. 50 transparency (chatbots, synthetic media, AI-generated content), governance (AI Office, AI Board), penalties (Art. 99), confirmed phase-in timeline (Digital Omnibus adopted June 29, 2026: Annex III deferred to Dec 2, 2027; Annex I to Aug 2, 2028), and cross-framework mapping to ISO 42001, NIST AI RMF, and GDPR. Use for any EU AI regulation, AI system classification, or AI compliance question. Current as of July 2026. GPAI enforcement powers activate August 2, 2026.
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。
AI咨询/销售的对话策略助手。当用户需要准备AI方案沟通、跟业务部门聊AI落地、写AI提案、应对客户异议、做AI培训破冰时使用。触发场景:"怎么跟老板聊AI"、"客户说AI不靠谱"、"准备一个AI方案汇报"、"帮我想想怎么推AI"、"业务部门不配合"、"AI项目怎么卖"、"demo之后怎么跟进"。也适用于AI咨询师、技术合伙人、CTO做内部AI推广。
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 email drip campaigns, nurture sequences, and automated email flows. Includes templates for welcome series, abandoned cart, re-engagement, product launch, and onboarding sequences. Trigger phrases: "email sequence", "drip campaign", "nurture sequence", "email flow", "welcome series", "abandoned cart emails", "onboarding emails", "email automation", "product launch emails", "re-engagement campaign", "send email", "send sequence".
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 responsive HTML email has to render correctly in every client — table-based structure, inline CSS, 600px max width, dark mode handling, quirks for Gmail, Apple Mail, Outlook and Yahoo, bulletproof buttons, and a pre-send test checklist, shipping a self-contained .html file to paste into Klaviyo, Mailchimp, HubSpot, or Brevo. Trigger on 'HTML email', 'code an email template', 'responsive email', 'why does my email break in Outlook', 'email dark mode is broken', 'the newsletter looks wrong on mobile'. Not for — sequence strategy and subject lines, see `14-email-marketing-global`; a web page, see `12-landing-page-brief-global`; brand colors and fonts, see `46-brand-guideline-global`.
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。
Get one actionable improvement for your AI product based on the latest GenAI PM briefs. Fetch the last 5 days of curated AI PM insights from genaipm.com, analyze the current repo/project, find synergy between trending topics and the user's work, then research the source material and apply a concrete improvement. Use when the user wants to improve their AI product, get coaching on AI PM best practices, apply the latest industry insights to their codebase, or run "/one-step-better-ai-pm". Requires a GenAI PM subscriber email (set GENAIPM_EMAIL env var or provide when prompted).
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。
Score a website's AI answer-engine visibility 0–100 against the open AIV rubric, and, with the user's own API keys, check and track through the OpenAI, Perplexity, Gemini and Anthropic APIs whether AI engines actually cite it. Use when the user wants to know whether AI engines can find, parse, trust and cite their site, or whether they do. Triggers on: 'does ChatGPT cite us', 'AI citation rate', 'share of voice in AI answers', 'track AI visibility weekly', 'AIV', 'AI visibility', 'GEO audit', 'generative engine optimization', 'AEO', 'llms.txt', 'will AI cite my site', 'AI search ranking', 'get cited by ChatGPT'.
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 combined DPIA and AI Act conformity assessment for AI systems processing personal data. Covers EDPB-EDPS Joint Opinion 5/2021, training data lawfulness under Art. 6 and Art. 9, Art. 22 automated decision-making, algorithmic bias detection, and NIST AI RMF MAP function. Keywords: AI privacy, DPIA, AI Act, algorithmic bias, automated decision-making, Art. 22, training data, NIST AI RMF.
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。
The new frontier of audio: AI-generated music with Suno and Udio, AI sound effects with ElevenLabs, AI voice cloning, and AI audio enhancement. This skill covers the full spectrum of neural audio synthesis and manipulation. We're in an era where a single person can produce broadcast-quality audio content that would have required studios, musicians, and engineers. AI doesn't replace musical talent—it democratizes production capability. Original compositions in minutes. Custom sound design in seconds. Voice in any language instantly. The practitioners of this skill understand both the creative potential and the ethical considerations. They know when AI audio enhances creativity and when it needs human touch. They're audio directors who orchestrate AI tools like instruments in a symphony. Use when "AI music, generate music, Suno, Udio, AI audio, AI sound, generate soundtrack, background music, sound effects, audio generation, jingle, AI score, stem separation, ai-audio, music, suno, udio, sound-effects, soundtrack, generation, audio-branding, production" mentioned.
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。
The intersection of AI generation and performance marketing. This skill covers creating ad creatives at scale using AI tools—from static images to video ads to dynamic creative optimization—while maintaining the conversion focus that performance marketing demands. Traditional creative testing is slow: create 5 variants, wait weeks for data, iterate. AI-powered ad creative is fast: generate 50 variants in an hour, test simultaneously, learn in days, iterate continuously. The constraint is no longer production capacity—it's testing velocity and creative strategy. This skill bridges AI generation capability with advertising effectiveness, ensuring that AI-created ads don't just look good—they convert. Use when "AI ads, ad creative, performance creative, ad generation, creative testing, ad variants, DCO, dynamic creative, Meta ads, Google ads, ad fatigue, conversion creative, advertising, performance-marketing, creative-testing, ai-ads, conversion, paid-media, scale" mentioned.
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。
AI 产品经理 (LLM 应用 / 生成式 AI / Agent 产品 / Copilot 嵌入 — 跨模型评估 / 工作流设计 / 产品-工程协同) (AI Product Manager — LLM application / generative AI / agent product 的产品经理实战) Master OS — automated mastery of AI Product Manager — LLM application / generative AI / agent product 的产品经理实战: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on AI Product Manager — LLM application / generative AI / agent product 的产品经理实战 problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词:「AI 产品经理」「AI PM」「LLM 产品」「Generative AI product」「RAG 产品」
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。