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Pre-fills a customer's or prospect's security or third-party risk questionnaire from the organisation's own answer sources (prior questionnaires, answer library, policies), returning one row per question with a draft answer marked Reused, Adapted, Missing or Routed, its source, date, scope match and owner, plus the Missing list by owner. Never invents an answer, certification or control and never submits. Use when the user asks to "pre-fill this security questionnaire", "take a first pass at the customer's due diligence form", "answer this vendor assessment from our previous responses", "populate the third-party risk questionnaire" or "which questions can we reuse answers for". Do not use for screening a vendor's own answers, use vendor-risk-screening-brief instead; for RFP or tender answers use rfp-response-drafter. Drafts for human review; never approves, authorises or signs off.

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Compares one clause (liability, termination, confidentiality or any other) across several contracts, templates or successive versions and returns a DRAFT comparison table: verbatim clause text per document, the clause split into elements with every difference from the baseline highlighted and categorised, and neutral questions for counsel. Never says which wording is better or enforceable. Use when the user asks to "compare the liability caps across these five supplier contracts", "line up the termination clause in these three drafts", "show how the confidentiality clause changed between versions", "contrast this clause with our template" or "benchmark the indemnity wording across our customer agreements". Do not use for a whole-contract review, use contract-review-pack instead; for screening one NDA against standard positions, use nda-triage. Drafts for human review; never approves, authorises or signs off.

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Reviews a proposal, business case, deck or plan in character as a Chief Data Officer archetype and returns a DRAFT review in the chat with a verdict, findings that cite the exact passage, data and AI governance risks, what would change the verdict and five interrogation questions. Use when the user asks to "run a CDO review", "pressure-test the data governance in this plan", "what would a CDO say about this", "check the metric definitions and data sources" or "prepare this for the data governance board". Do not use for security controls or third-party security risk, use ciso-reviewer instead; for contract, liability or regulatory terms, use general-counsel-reviewer. Drafts for human review; never approves, authorises or signs off.

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Flags where a P&ID draft raises a process safety question and points to the candidate evidence an engineer would review (HAZOP register, relief study, SIL assessment, isolation philosophy), as questions and quoted passages with UNKNOWN for missing documents, plus safety functions, relief devices and isolation requirements carried over as stated. Never rates, sizes, classifies, resolves or declares protection adequate. Use when the user asks to "write the process safety flags", "produce the process safety section of the P&ID enrichment", "list which protection questions this P&ID raises" or "map the HAZOP and relief study evidence to the draft" after gate G2, once the piping and instrumentation sections exist. Do not use for proposing loops, alarms or trips from the control philosophy, use instrumentation-and-control-enrichment instead; do not use for checking identifiers, use tagging-and-numbering. Drafts for human review; never approves, authorises or signs off.

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Reviews a proposal, business case, deck or plan in character as a Chief Technology Officer archetype and returns a DRAFT review in the chat with a verdict, findings cited to the exact passage, technology risks (architecture, build versus buy, vendor lock-in, security of design, engineering capacity), what would change the verdict and five interrogation questions. Use when the user asks to "run a CTO review", "pressure-test the technical side of this plan", "what would a CTO ask about this" or "rehearse the technology seat before the review". Do not use for cash, payback or budget questions, use cfo-reviewer instead; for capacity and timeline questions, use coo-reviewer; for security controls, privacy or compliance, use ciso-reviewer. Drafts for human review; never approves, authorises or signs off.

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4人の異なる専門家ペルソナ（20年ベテランエンジニア、TDDエキスパート、Clean Codeエキスパート、バグハンター）で ソースコードを批判的にレビューするスキル。設計判断、テスト容易性、可読性、バグ検出の観点から コードの問題を検出し、改善提案を行う。Python/JavaScriptに対しては追加のチェックポイントを適用。 バグハンターは状態遷移、例外パス、依存関係、非同期競合に特化し、本番環境での問題を事前に検出する。 Use when reviewing source code from multiple expert perspectives to find design flaws, testability issues, code quality problems, and runtime bugs. Triggers: "critical code review", "multi-persona code review", "expert code review", "code quality assessment", "find bugs".

Audit a dataset or access rule before it joins an identity-graph build (access rules behave like datasets in NQL here). Enumerates failure modes (hub identifiers, high-degree nodes, suspicious values, over-connected identifiers), tests hypotheses in parallel, quantifies damage by rows / edges / entities, and proposes minimal filters ranked by severity. When issues are found, returns a validated `CREATE MATERIALIZED VIEW` NQL the caller can run to produce a graph-ready clean source; if the data passes, says so and recommends it unchanged. Plans and authors the clean-view NQL; does not execute it. Use when: "audit this dataset before the graph build", "find bad edges in <source>", "check identity data quality", "recommend filters for the graph build", "quantify damage from <identifier_type>", "pre-graph DQ". (narrative-identity)

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Produce a coverage & quality profile of a Narrative dataset (or access rule): row count, per-column null/fill rate, cardinality, ranges, top-values, inferred column shape, and quality flags. Reads bundled stats + sample first, recovers missing/stale stats by configuring and recalculating them, and escalates to a cheap `/write-nql` query only for a measure no stat can provide. Descriptive, not prescriptive. Use when: "profile dataset N", "what does dataset N look like", "coverage and quality of <dataset>", "what id types does N emit", "null rates / cardinality for <dataset>", "is this dataset's stats fresh". (narrative-common)

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Knowledge pack synthesized from JSP 376 Defence Acquisition Safety Policy V1.1 (April 2024, Ministry of Defence, Open Government Licence v3.0): acquisition safety requirements, safety artefacts, and their application across the standard acquisition lifecycle. Covers the policy frame and legislative baseline, SRO and User responsibilities, safety management and safety requirements, test and evaluation and the safety case, supervision and approvals decision support, and the seven lifecycle phases. SCOPE LIMITS: single-source (JSP 376 V1.1); MOD policy and guidance, not statute; builds on JSP 815 and cites JSP 655, neither reproduced here (use jsp-815 for the SMS); Chapter 4 (Non-Standard Acquisition) is unpublished in V1.1 and is not in this pack; no DEF-STAN text (Def Stan 00-056 is named, not quoted); no other JSP reproduced. Reconstructed reference notes, not MOD guidance, and no official status.

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Apply a Style to any artifact in the workspace (presentation, card, poster, social post, web page). Use when the user says "apply style X", "render this with style X", or wants to reuse a saved style on a new piece.

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Run an extremely strict maintainability review for abstraction quality, giant files, and spaghetti-condition growth. Use for a thermo-nuclear code quality review, thermonuclear review, deep code quality audit, or especially harsh maintainability review.

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Knowledge base from the NIST Framework for Cyber-Physical Systems (SP 1500-201/202/203, v1.0, 2017). Use for engineering and analyzing cyber-physical systems (CPS) and IoT: the CPS Framework's aspect × facet grid (nine aspects of concern examined through conceptualization, realization, and assurance facets), cross-property trustworthiness risk management (safety/security/privacy/reliability/resilience together), data interoperability (syntactical/semantic/contextual, canonical models, identifiers, provenance), the timing aspect (time-interval classes, time domains, time-aware networking) and secure/resilient time (GNSS jamming/spoofing, PTP/NTP attacks, holdover, the clock-error model and Allan/MTIE metrics), plus the use-case requirements method. Bridges IT and OT under a clock. Scope limits: a 2017 living/draft document, thin on post-2017 standards and on detailed control catalogs; it names but does not reproduce ISO/IEC/IEEE 42010 and 15288 process text or permission-licensed third-party figures.

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Knowledge base from MIL-STD-882E (DoD System Safety). Use for the system safety process, hazard analysis tasks (PHA/SSHA/SHA/O&SHA), the risk assessment matrix (severity x probability), software safety criticality, and risk acceptance. US-gov public domain.

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Knowledge base from the DoD M&Q BoK (the Manufacturing and Quality Engineering Body of Knowledge), v3.0 of July 2025, published by OUSD(R&E). Use for the manufacturing-and-quality view of the defense acquisition life cycle: what M&Q engineers do across the Adaptive Acquisition Framework phases (Pre-MDD, Materiel Solution Analysis, Technology Maturation and Risk Reduction, Engineering and Manufacturing Development, Production and Deployment, Operations and Support); the twelve M&Q threads (A–L) built on the '5 Ms'; manufacturing feasibility and producibility; Manufacturing Readiness Levels and assessments; Key/Critical Characteristics and process capability (Cp/Cpk, SPC); the standards stack (AS6500, AS9100/ISO 9001, AS9103, AS9145); technical reviews (ASR/PDR/CDR/PRR) and milestone gates; DCMA surveillance; industrial base and supply chain; and sustainment (LCSP, IPS, ILA, ISR). Scope is DoD acquisition M&Q practice on the Major Capability Acquisition path — it is a best-practice compilation, not policy, and is thin on detailed shop-floor process engineering, contract law, and the full text of the cited industry standards (which it names but does not reproduce).

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Knowledge base from the DoD Manufacturing Readiness Level (MRL) Deskbook (Version 2022, OSD ManTech / Joint Service–Industry MRL Working Group). Use for assessing and managing manufacturing maturity and producibility risk in defense acquisition: the 10-level MRL scale and its non-linear, target-not-grade nature; the five demonstration environments (laboratory → production-relevant → production-representative → pilot line → production line); the nine manufacturing-risk threads and sub-threads; how MRL targets map onto Adaptive Acquisition Framework milestones (MRL 4/6/7/8/9); conducting an MRL Assessment; building a Manufacturing Maturation Plan; putting MRL maturity into contract language (Section L/M, SOW, AS6500A, DIDs); tailoring criteria for S&T, single-system, ship, sustainment, and industry contexts; and screening operational-technology cybersecurity. Manufacturing-readiness focused — it measures producibility risk and frames mitigation; it is NOT a technology-readiness (TRL) guide, a full systems-engineering process model, a cost-estimating or schedule guide, or a deep cybersecurity audit method (see sibling packs for those).

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MMI評価エージェント - Modularity Maturity Indexによるモジュール成熟度評価（Cohesion/Coupling/Independence/Reusability）。/evaluate-mmi [対象パス] で呼び出し。

Operational guide for the NV oOS assistant export/import track — the canonical nvoos-assistant bundle format (v1), the shared portability engine, its five surfaces (WP-CLI, REST, admin UI, AI tools, backup provider), the Pro blueprint exporter, credential-redaction rules, legacy/blueprint import compatibility, test conventions, and the Content Graph port checklist. Use when extending or debugging assistant export/import, adding a surface, changing the bundle schema, fixing round-trip fidelity, or continuing the portability track ("continue the portability plan", "add assistant export to X").

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Use when the user asks to "map our positioning", "name our competitive alternatives", or "pick a beachhead segment for the launch"; produces a Dunford-style positioning canvas — named competitive alternatives (including spreadsheet and status quo), unique attributes (verifiable, or routed to the claims ledger), value themes (attribute→benefit→value chains), a target beachhead segment scored on serviceability / pain intensity / reachability, and a one-sentence onlyness statement — the sole upstream of the message house and the entity-signal source for the canonical entity profile. Not for the message house or per-channel launch copy — use message-house-builder; not for audience/persona profiling itself — use audience-mapper; not for SEO keyword positioning — use keyword-research. 定位画布/竞争替代品/独特价值/滩头细分

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Use when auditing domain authority, trust, or citation credibility; runs a peer-relative 40-item CITE profile with evidence coverage and verified manipulation/penalty veto checks. Not for page-level content quality — use content-quality-auditor; not for backlink profiling alone — use offsite-signal-analyzer. 域名权威/网站可信度

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セキュリティ観点の通常レビューエージェント。 基本的なセキュリティチェック、認証・認可設計、プライバシー設計の個別スキルへルーティングする。 repository / subsystem の明示的な security audit は river-review-security-audit へ委譲する。

Repository または subsystem を対象に、source-only で明示的なセキュリティ監査を行う entry skill。 通常の PR セキュリティレビューとは分離し、reconnaissance、scope 固定、既存 security skill への委譲、 evidence と unresolved hypothesis、observe-only SecurityAuditCoverage、coverage critic、 structured audit artifact と repeat-run coverage を扱う。target-controlled code は実行しない。

Interactive Domain-Driven Design modeling sessions based on DDD Distilled (Vaughn Vernon) and Domain Modeling Made Functional (Scott Wlaschin). Guides users through strategic and tactical design via 13 phases: discover, storming, contexts, mapping, aggregates, events, validate, glossary, workflows, types, simulate, publish, sync. Phase 13 (sync) reconciles divergences found by --analyze between the domain model and the implementation — judging whether the model or the code is authoritative, then planning and implementing the fix and re-aligning the model. Phases 9-11 take the conceptual model from phases 1-8 and produce workflow pipeline designs, compilable type definitions (TypeScript, Kotlin, Scala, Rust, C#, F#), workflow verification via type-level tests, and automatic UI field enumeration from the domain model. Phase 12 (publish) renders all docs/domain artifacts into one self-contained, cross-linked HTML site (separate files joined by a shared nav). Each phase is an interactive dialogue where AI acts as facilitator and domain expert challenger. Use when: "DDD", "ドメイン設計", "ドメインモデリング", "Event Storming", "Bounded Context", "集約設計", "ユビキタス言語", "コンテキストマップ", "ワークフロー設計", "パイプライン設計", "ステップ分割", "中間型", "型駆動フロー", "型駆動設計", "Domain Modeling Made Functional", "Railway Oriented Programming", "入力画面項目", "フォーム項目洗い出し", "UI 項目抽出", "HTMLにまとめる", "ドキュメントサイト化", "成果物を1つのHTMLに", "publish", "モデルと実装の差異", "差異解消", "実装との乖離", "モデルとコードを一致", "差異の実装計画", "sync", "複数フェーズを逐次実行", "フェーズをまとめて実行", "/ddd run", "サブコマンド一覧", "/ddd list", "/ddd", "ドメイン分析したい", "モデリングしたい", or any domain design / type modeling activity.

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Hive CE (Community Edition v2.19.x) NoSQL object database for Flutter providing blazing-fast key-value and object storage with TypeAdapters. Use this skill when implementing offline-first architecture, high-performance local data caching, NoSQL document-style object stores, custom TypeAdapter serialization for complex objects, lazy loading boxes for memory efficiency, encrypted boxes (HiveAES encryption), database compaction for size optimization, storing large datasets without SQL schema overhead, implementing local-first sync patterns, or migrating from SQLite to NoSQL. Supports primitive types, custom objects, lists, and maps. Ideal for apps requiring ultra-fast read/write operations (microsecond latency), object persistence without ORM complexity, or local-first data architecture.

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ジェネリクス、条件型、マップ型、テンプレートリテラル、ユーティリティ型を含むTypeScriptの高度な型システムを習得し、型安全なアプリケーションを構築します。複雑な型ロジックの実装、再利用可能な型ユーティリティの作成、TypeScriptプロジェクトでのコンパイル時型安全性の確保時に使用してください。