2,449 件 ・ 関連度順
概要と使いどころ
/cs:ai-act-readiness <system> — EU AI Act 6-question forcing interrogation. Use during AI-system intake, before EU deployment, or during annual compliance refresh as Article 113 obligations phase in (2025-02-02 / 2025-08-02 / 2026-08-02 / 2027-08-02).
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。
Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.
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 underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
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。
PCI DSS 4.0.1 compliance audit support skill. Provides expert guidance for Cardholder Data Environment (CDE) scoping, gap analysis, audit preparation, SAQ completion support, and remediation planning. Includes SOC 2 mapping for combined audit efficiency. Use when preparing for PCI DSS audits, conducting gap analysis, creating remediation plans, or answering SAQ questionnaires for payment card compliance.
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 creating bug/defect reports during system testing. Use this skill when you discover a bug, need to document test failures, or want to create comprehensive bug tickets with proper reproduction steps, severity assessment, and environment details. Guides users through interactive questioning to gather all necessary information and generates professional bug ticket documents in Markdown format. Supports Japanese (default) and English.
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 critiquing a system design across correctness, scalability, reliability, maintainability, and observability using probe-first questioning.
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 learner benefits from guided questioning to build reasoning and uncover misconceptions before receiving direct answers.
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, validate, and (optionally) execute an NQL query against a Narrative dataset. Drafts the query from the user's question, runs `narrative_nql_validate` until it compiles, explains the query in plain English, and only runs it on explicit approval (or when invoked with `--run`). Use when: "write an NQL query for X", "query this dataset", "validate this NQL", "run NQL against dataset <id>", "how many rows match Y", "show me the top N records from <dataset>". (narrative-common)
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。
Compare your data to a partner's data in the marketplace. Given a dataset you already own with person/edge data, this skill walks you through picking a partner data source to match against, choosing which identifier types to match on, optionally selecting which enrichment attributes to attach, and then submits the report — returning overlap, match counts, and demographic coverage. Use when: "how does my data compare to your marketplace", "compare my data to [partner]", "how much overlap do I have with [supplier]", "run a match report", "match my customers against 3P data", "see what enrichment is available for my dataset", or any open-ended question about marketplace overlap. (narrative-identity)
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 the document of a research run — plan the question and the outline with rs_plan, write prose and declare its claims together with rs_write, choose the claim strength the evidence actually holds, follow the section structure the run's kind maps to, read the draft back, and build a watermarked draft before the gated clean build. Use when a run's document has to be written, a section drafted, a claim bound to a source, or a build attempted.
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。
Choose the design and the numbers a research run can honestly claim — write the structured METHOD RECORD (databases, date of access, search string, criteria, screening counts) that r0 validates, pick the claim strength a design can actually carry, record a statistic as data rather than prose, route to the reporting guideline the design owes, and decide what to preregister. Use when a run's question, design, search or statistics have to be settled before the writing, or when a claim needs a strength or a number attached to it.
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。
Interview the user deeply about a plan, probing technical implementation, UI/UX, risks, tradeoffs, and missing decisions before writing or refining a spec. Use when the user says "interview me" or asks to be questioned about a plan.
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。
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
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。
Clarify ambiguous or conflicting requests by researching first, then asking only judgment calls. Use when prompts say "grill me", ask hard questions, request relentless interrogation, pressure-test assumptions, clarify scope/requirements, define success criteria, or request system-design/optimization decisions before implementation; stop before implementation.
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。
Conduct a Marty-Cagan-style opportunity assessment interview and produce a ~2-page Opportunity Brief in Confluence. Covers business objective, customer, problem, success metric, current alternatives, assumptions/risks, and what we don't know yet. Triggers on "opportunity brief", "opportunity assessment", "discovery brief", "who is this for", "why are we building this", "validate this idea", "product discovery", or any request to frame a feature before implementation. One question at a time. Records accepted research gaps as structured Confluence Decision pages with bidirectional links.
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。
Collapse meaningful ambiguity with contrastive examples. Use when a plan/design has several plausible meanings, requirements feel vague, examples would clarify intent faster than grilling, or the user asks to disambiguate, find ambiguity, use behavioral kernels, or ask contrastive questions.
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。
Author a completed-spec fixture — a seeded intent graph plus a believable four-phase interview transcript — for a brunch feature, so it can feed any downstream tooling that consumes a completed spec or dogfood the UI. Use when you need a real completed specification in .brunch/brunch.db for testing or demo: pick a feature from memory/SPEC.md (or a free description), choose a stress profile (coverage|clean), and produce a registered scenario seed + an interview-questions doc that match exactly.
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。
Time-boxed throwaway investigation to answer one hard question. Use when facing technical uncertainty before committing to a frontier item or scoped slice — the output is knowledge, not production code.
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。
Monitor PR review comments and automatically classify and address reviewer feedback including code changes, questions, and nits. Use when handling PR reviews, addressing reviewer comments, responding to code review feedback, or automating review resolution. Triggers on handle reviews, PR review, address feedback, reviewer comments, code review, review response.
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。
Knowledge base from the GAO Agile Assessment Guide (GAO-24-105506, 2023). Use for assessing and managing Agile software development in federal programs: the Agile Manifesto and framework family (Scrum, Kanban, XP, SAFe, DA, DSDM, Lean, DevOps); the three adoption perspectives (team dynamics, program operations, organization environment); requirements decomposition (epics, features, user stories, INVEST, MoSCoW, definition of done); Agile-aware federal contracting (FAR, modular contracting, SOO/PWS/SOW, product owner vs. COR); program monitoring and control (WBS, cost, schedule, EVM at the feature level); Agile metrics (velocity, lead/cycle time, CFD, burn charts); and the auditor's key-question bank. Oversight- and acquisition-oriented: it tells you how to *assess and govern* Agile programs, not how to code. Thin on hands-on engineering practice, deep cost/schedule checklists (see gao-cost, gao-schedule), and any non-US-federal context.
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。
ドゥ・シェーザーとバーグによる解決志向ブリーフセラピー（SFBT）：ミラクル・クエスチョン、例外の探索、スケーリング、リソースの活性化。
Ориентированная на решение краткосрочная терапия по де Шейзеру и Берг: Чудо-вопрос, исследование исключений, шкалирование, активация ресурсов.
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。
德·沙泽尔与伯格的焦点解决短期心理治疗（SFBT）：奇迹提问、例外探索、评定量表、资源激活。
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。
Terapia Breve Centrada en Soluciones según de Shazer y Berg: Pregunta del milagro, exploración de excepciones, escalamiento, activación de recursos.
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。