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Build a vulnerability exception and risk acceptance tracking system with approval workflows, compensating controls documentation, and expiration management.

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Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery efforts. Covers AES, RSA, ChaCha20, and hybrid encryption schemes. Activates for requests involving ransomware cryptanalysis, encryption analysis, key recovery assessment, or ransomware decryption feasibility.

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Check whether this card's code meets the acceptance criteria

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This skill should be used when creating UAT (User Acceptance Testing) test cases in Excel format for Salesforce CRM projects. It generates standardized test case documents with summary sheets and detailed test case lists, following a specific format structure with test case ID, priority, category, scenario, preconditions, test steps, expected results, and acceptance criteria.

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기능의 external behavior를 Cucumber 인수 테스트(주 검증층)로 구축 — .feature 실행으로 문서↔코드 드리프트를 구조적으로 차단, Four Layer(Steps→Protocol Driver→SUT), 태그 기반 가역 제외, 기존 JUnit 인수 테스트 이관. "인수 테스트 도입", "Gherkin을 실행 가능하게", "cucumber 셋업" 요청 시 사용. /cucumber-acceptance로 호출.

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Write acceptance criteria for a Jira story using Given/When/Then scenarios. Use this skill when the user asks to write AC, acceptance criteria, write scenarios, improve a story, add AC to a ticket, or mentions a Jira ticket and wants better requirements. Also triggers on "write better AC", "this story needs AC", "add scenarios to this ticket", or when reviewing a Jira story for completeness.

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Terapia de Aceptación y Compromiso (ACT) según Steven Hayes: modelo Hexaflex con los seis procesos nucleares de la flexibilidad psicológica.

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Acceptance & Commitment Therapy (ACT) according to Steven Hayes: Hexaflex model with the six core processes of psychological flexibility.

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Acceptance & Commitment Therapy (ACT) nach Steven Hayes: Hexaflex-Modell mit den sechs Kernprozessen psychischer Flexibilität.

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Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

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Use when the user asks to "codify our brand voice", "define naming rules for our products and tiers", or "write the tone-of-voice guide with banned phrases"; produces the brand-level voice canon (register, tone spectrum, banned-phrase list, few-shot examples drawn only from the brand's own published material) and the naming tax (product / feature / tier naming rules plus approved and banned terms) that seeds the narrative-registry canon and that every channel's voice adaptation points up to. Not for per-platform voice adaptation — use channel-registry's voice-dossier; not for finished copy or blog posts — use content-writer; not for the message hierarchy itself — use message-system-architect; not for claim adjudication — use offer-claims-registry. 品牌语气/词汇表/命名税/禁用词/品牌语言规范

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Ensure requirement docs define scope, terminology, acceptance criteria, edge cases, and non-functional requirements.

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Expert en localisation d'agents IA (i18n, l10n, RTL, adaptation culturelle, arabe DZ/darija)

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Accounting Specialist IA — Expert en comptabilité (bookkeeping, tax DZ, invoicing, CCP, facturation algérienne)

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Use when a coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

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 a vulnerability exception and risk acceptance tracking system with approval workflows, compensating controls documentation, and expiration management.

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。

Analyzes encryption algorithms, key management, and file encryption routines used by ransomware families to assess decryption feasibility, identify implementation weaknesses, and support recovery efforts. Covers AES, RSA, ChaCha20, and hybrid encryption schemes. Activates for requests involving ransomware cryptanalysis, encryption analysis, key recovery assessment, or ransomware decryption feasibility.

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。

Write clear, testable acceptance criteria in Given-When-Then format following INVEST principles and BDD best practices.

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Windows アプリ開発 (Windows App SDK / WinRT) の OS 統合 API リファレンス。 DeviceInformation, DeviceWatcher, センサー (Accelerometer, Gyrometer, Compass, OrientationSensor, Pedometer, ActivitySensor), Bluetooth LE, USB, Serial, HID, Battery, HttpClient, StreamSocket, WebSocket, BackgroundDownloader/Uploader, NetworkInformation, PointerInput, KeyboardInput, FocusManager, DragAndDrop, IME/TextInput, Calendar, DateTimeFormatter, CurrencyFormatter, ResourceLoader (多言語化・地域化), PasswordVault, CryptographicBuffer, WindowsHello/Passkeys, WebAuthenticationBroker, Clipboard, DataTransferManager, Launcher, JumpList, TaskbarManager, SecondaryTile, StartupTask, ProtocolActivation。

Work out the order and the loose ends before turning down an offer or withdrawing from a selection process: whether the offer being kept is actually settled in writing, whether each decline is mid-selection, post-offer, or after acceptance, who besides the employer has to be told when the application came through an agent, a school recommendation, or a referral, which reply deadlines have passed, and what documents, expenses, or borrowed items are still outstanding. Use when a user holds more than one offer and needs to decline the rest, wants to withdraw from a process they are no longer pursuing, or has been asked to turn down other employers as a condition; do not use to decide whether to decline, to rule on what declining after acceptance means legally, or to send any message.

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Tests genotype-environment associations and identifies adaptive loci while correcting for the four-confound landscape (structure, demography, background selection, sampling design) using LFMM2 with mandatory K via sNMF cross-entropy elbow (LEA 3), BayPass Core/AUX/C2/IS with Omega covariance matrix, RDA / pRDA for polygenic adaptation (Forester 2018; requires imputed genotypes), OutFLANK with trimmed FST null, pcadapt, gradient forests (Ellis-Smith-Pitcher 2012, NOT mis-cited Ellis-Manel), Capblancq & Forester 2021 RDA Swiss-army-knife, genomic-offset prediction with Lind & Lotterhos 2025 three-regime caveat, Lotterhos-Whitlock sampling optima, Wang & Bradburd 2014 IBD vs IBE, and Circuitscape + ResistanceGA. Use when identifying adaptive loci across gradients, choosing K for LFMM2, deciding among GEA methods, predicting maladaptation with the novel-environment caveat, distinguishing IBD vs IBE, or optimizing sampling design.

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 coding task should be driven end-to-end from issue intake through implementation, review, deployment, and acceptance verification with minimal human re-intervention.

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。

Write and refine high-quality user stories — INVEST criteria, "As a X, I want Y, so that Z" format, Gherkin acceptance criteria when applicable, definition of ready, anti-patterns, and a review checklist. Use when creating or reviewing user stories, PRD section 6, backlog items, or acceptance criteria. Do NOT use for technical specs, architecture decisions, or task decomposition.

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Analyzes development requirements and generates structured acceptance criteria for AEM Edge Delivery Services (EDS) tasks. Use when the user needs to define acceptance criteria, write requirements, scope work, or create a definition of done for EDS blocks, components, variants, bug fixes, or styling changes. Produces task breakdowns, identifies edge cases, and documents analysis for new blocks, variants, behavior modifications, CSS-only changes, and bug fixes.

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。