「systems」の検索結果

Knowledge base from the Expanded Guidance for NASA Systems Engineering (NASA/SP-2016-6105-SUPPL, Volume 1, March 2016) — the practitioner-depth supplement to the NASA SE Handbook. Use for the load-bearing mechanics the handbook compresses: the SE Engine's per-phase cadence and the iterative-vs-recursive distinction, the AS9100 crosswalk, life-cycle tailoring vs. customization and the Compliance Matrix, the recursive system-design consistency loop (ConOps vs. Operations Concept, requirement flow/type/ownership, successive refinement), product realization (verify/qualify/accept/certify cardinality, protoflight, 'test the way we fly' coverage, two-form transition), and the crosscutting technical-management procedures (six-step scheduling, cost-estimating method selection, JCL, interface document family, RIDM/CRM, CM baselines, EVM arithmetic, MOE/MOP/KPP/TPM, the three required leading indicators, and the decision-analysis method catalog). This is the DEPTH layer — it deliberately does NOT restate the base definitions; pair it with the nasa-se-handbook pack. Scope: NASA space-flight SE practice (Vol 1 Practices); thin on the Vol 2 process-appendix detail, on non-NASA/commercial life cycles, and on software-engineering methodology.

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Knowledge base from the DoD Test & Evaluation Enterprise Guidebook (OUSD R&E, August 2022). Use for DoD test and evaluation (T&E) across the Adaptive Acquisition Framework — the four test communities (contractor testing, developmental DT&E, operational OT&E, live-fire LFT&E); the five operational events (Operational Demonstration, EOA, OA, IOT&E, FOT&E) and the OTRR gate; the T&E Strategy / TEMP and its IDSK, with the upstream documents that feed it and the test plans that decompose it; the T&E organizations and oversight roles (USD(R&E), DOT&E, TRMC, the Service Executives and OTAs, the T&E WIPT, CDT); and pathway-specific T&E for all six acquisition pathways (Urgent Capability, Middle Tier, Major Capability, Software, Defense Business Systems). Statutory anchors include 10 U.S.C. §4171 (IOT&E) and §4172 (LFT&E/FUSL). This is guidance, not policy: it points outward to DoDI 5000.89 and the DoDI 5000-series for binding detail, and is thin on detailed test statistics/design-of-experiments methodology, cost estimating, the Acquisition of Services pathway, and any CUI/CAC-gated companion guides.

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Knowledge base from MIL-HDBK-338B (Electronic Reliability Design Handbook). Use for electronic reliability engineering: R/M/A theory, reliability specification/allocation/prediction, parts management and derating, reliable circuit and fault-tolerant design, environmental and human performance reliability, FMEA/FMECA/FTA/sneak circuit analysis, design reviews and testability, FRACAS, reliability demonstration and growth testing, and systems-level R&M parameters. Covers selected Part 2 design-guidance topics only; skips large annex/part-stress tables. Guidance handbook — not a contractual requirement text. Does not replace MIL-HDBK-217 prediction libraries, service-specific reliability regs, or safety standards (see mil-std-882).

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Knowledge base from DoD Architecture Framework (DoDAF) 2.02 — Volume II: Architectural Data and Models. Use for DoDAF viewpoints, DM2 meta-model, capability modeling, operational architecture, systems architecture, services architecture, data/information modeling, standards compliance, project/portfolio integration, and fit-for-purpose model selection. Does not cover DoDAF Volume I (policy/governance) or Volume III (enterprise-level guidance); also does not substitute for the live DISR or DARS registries.

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Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.

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Master authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing APIs, or debugging security issues.

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Build automated billing systems for recurring payments, invoicing, subscription lifecycle, and dunning management. Use when implementing subscription billing, automating invoicing, or managing recurring payment systems.

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Master authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing A...

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Use when working with Aws Fsx — aWS FSx file system management and health analysis. Covers FSx for Lustre, Windows File Server, NetApp ONTAP, and OpenZFS file systems, volumes, backups, data repository associations, and storage capacity metrics. Use when inspecting FSx file systems, debugging performance issues, reviewing backup configurations, or analyzing storage utilization.

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54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.

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Master authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing APIs, or debugging security issues.

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Expert en systèmes distribués v2 (CAP, consensus, partitions, consistence événuelle, patterns)

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Expert en systèmes distribués (CAP theorem, consensus, partitions, vector clocks)

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Design de produto nivel Apple — sistemas visuais, UX flows, acessibilidade, linguagem visual proprietaria, design tokens, prototipagem e handoff. Cobre Figma, design systems, tipografia, cor, espacamento, motion design e principios de design cognitivo.

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Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.

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Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-review.

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Hostile self-review of recently written AI workflow code that then applies fixes (agents, tools, chat context, summarization, tokens, attachments). Use after generating AI systems code, or when asked to self-review and harden it. Not for PR peer review (code-review) or no-edit devil's-advocate attacks (adversarial-challenge). Prefer: adversarial-challenge → decide → this skill.

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Design patterns for building autonomous coding agents. Covers tool integration, permission systems, browser automation, and human-in-the-loop workflows. Use when building AI agents, designing tool APIs, implementing permission systems, or creating autonomous coding assistants.

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You are a cognitive architect who understands that memory makes agents intelligent. You've built memory systems for agents handling millions of interactions. You know that the hard part isn't storing - it's retrieving the right memory at the right time.

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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.

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Vite build systems: production-level ESM, assets, chunk strategies and commands. Use when implementing, reviewing or testing vite build systems for React, Vite, Next.js or Perfect_AI projects.

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GLSL shader systems: production-level uniforms, color space, derivatives, precision. Use when implementing, reviewing or testing glsl shader systems for React, Vite, Next.js or Perfect_AI projects.

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This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.

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