'systems' 검색 결과

Knowledge base from the FAA Requirements Engineering Management Handbook (DOT/FAA/AR-08/32). Use for writing requirements for real-time, embedded control systems — the avionics/medical slant — via the Handbook's eleven recommended practices: system overview and boundary (monitored/controlled variables), operational concepts (use cases), environmental assumptions, change-tolerant functional architecture (dependency diagrams), safety-driven architecture revision (FHA/PSSA/fault tree), system modes, detailed behavior and performance requirements (ideal value + tolerance + latency), the four-variable model bridge to software requirements (MON/CON/NAT/REQ, IN'/REQ'/OUT', DO-178B mapping), subsystem allocation, and rationale. Carries the Isolette Thermostat and Flight Control System worked examples. Slanted toward control systems with sensors and actuators; thin on information-system / enterprise / agile requirements, on requirements-management tooling, and on the formal-methods internals of SCR/RSML/SpecTRM (it names them, does not re-teach them). Does not reproduce the IEEE/DO-178B/ARP standards it cites.

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Knowledge base from the FAA Human Factors Design Standard (HF-STD-001B, 2016) — the FAA's consolidated human-factors / human-systems-integration design criteria for systems it manages, operates, or maintains. Use for requirement-level design rules on: general human-factors design principles; automation and function allocation; designing equipment for maintenance; displays, controls, and visual indicators; alarms, audio, and voice communications; the computer-human interface (information presentation, coding, interaction styles, windows, dialogue); keyboards, input devices, and workstation/workplace ergonomics; system security, personnel safety, environment, anthropometry, and user documentation; plus intended-use and tailoring guidance. It is a quantified, source-attributed synthesis (heavily citing MIL-STD-1472G, MIL-HDBK-759C, DOD-HFDG-ATCCS, NUREG-0700, NASA-STD-3000, ANSI, OSHA, ISO 9241). Complements nasa-hsi as a parallel HSI tradition from the civil-aviation domain. Scope limits: it is design criteria, NOT an HSI lifecycle/process model (use nasa-hsi, nasa-npr-7123, or dau-se-guidebook for process); it does NOT reproduce the third-party standards it cites; it is FAA-acquisition-oriented (ATC, towers, TRACONs, airway facilities), not a general consumer-UX guide; and it is thin on modern touchscreen/mobile, web, and AI-driven interface patterns and on quantitative human-reliability analysis.

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Knowledge base from the FAA Systems Engineering Manual (SEM) v1.0.1. Use for civil-agency systems engineering as the FAA practices it inside the Acquisition Management System (AMS) and the National Airspace System (NAS): the five-phase AMS lifecycle and its decision points; operational concept development and implementation-free functional analysis (ConOps, FFBD/N², CMLs); requirements analysis and architectural design synthesis (PRS→MRS, the PRD ratchet pPRD→iPRD→fPRD, RAM, ISEF/DoDAF views, CPRs); the seven technical management disciplines (Integrated Technical Management/SEMP, Interface Management/IRD-ICD, Risk-Issue-Opportunity, Configuration Management, SE Information Management, Decision Analysis, Verification & Validation); and the specialty disciplines (RMA via Service Threads/STLSC, Life Cycle Engineering, E3/Spectrum, Human Factors, Information Security via the NIST RMF, System Safety via the SMS, and Hazardous Materials/Environmental/EOSH). Scope limits: this is FAA-specific guidance, not policy — it is a tailorable menu that points outward to companion handbooks (FAA-HDBK-006A for RMA, the SMS Manual, the NIST 800-series) rather than restating generic SE theory; it is thin on detailed cost estimating, contracting/FAR law, software-development methodology, named anti-pattern catalogues, and any non-FAA or non-civil-aviation lifecycle. Source has no page numbers in the extracted text (~360 pp.).

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Knowledge base from the NASA Systems Engineering Handbook (NASA/SP-2016-6105 Rev 2). Use for NASA's systems-engineering process model — the SE Engine and 17 common technical processes, the program/project life cycle (Pre-Phase A through F), Key Decision Points and technical reviews (MCR/SRR/PDR/CDR/…), stakeholder expectations, technical requirements, design solution, product verification and validation, and crosscutting technical management (planning, risk, configuration, interfaces, data, assessment, decision analysis). Strong for aerospace/spaceflight project SE and lifecycle gating; NASA-specific terminology (KDPs, NPR 7123.1).

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Knowledge base from NASA-STD-8729.1A — NASA's R&M (Reliability and Maintainability) standard covering spaceflight and support systems (Revision A, 2017-06-13). Use for NASA's objectives-driven R&M framework — the R&M objectives hierarchy (one Top Objective decomposed into four sub-objectives, paired with tailorable strategies), how R&M requirements are established inside the SMA Plan required by NPR 7120.5, the SMA Technical Authority concurrence/independent-evaluation governance, milestone vs. readiness review gates, the reliability/maintainability/availability vocabulary (Ai vs. Ao, the failure causal chain, risk as a triplet), and the R&M Evidentiary Methods catalogue (FMEA/FMECA, FTA, RBDA, RCM, LORA, plus the space-environment and parts-pedigree analyses). Scoped to NASA spaceflight and support systems and to assurance planning: it is an objectives-and-strategies standard, so it deliberately does NOT prescribe step-by-step analysis procedures (those live in the referenced NASA Preferred Reliability Practices) and is thin on facility R&M, detailed math/derivations, and non-NASA or commercial life cycles.

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Knowledge pack from 'Towards Digital Engineering: The Advent of Digital Systems Engineering' (Huang et al., Old Dominion University, arXiv:2002.11672, 2020). Use when reasoning about digital engineering, the DoD Digital Engineering Strategy and its five goals, the Authoritative Source of Truth, digitalization vs. digitization, digital augmentation, digitalized models, provenance, unique identification, and the four-level (vision/strategy/action/foundation) DSE research framework. Covers the conceptual/vision layer of the field. SCOPE LIMITS: this is a single ~28-page vision paper, not a methods handbook — it is thin on step-by-step procedures, tooling, case studies, and quantitative evaluation, and it predates 2020 so it does not cover later digital-engineering standards or recent AI/LLM advances. Use the sebok pack for established SE canon and MBSE depth.

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Knowledge base from the OUSD(R&E) guidebook Implementing a MOSA in DoD Programs (Feb 2025). Use for the Modular Open Systems Approach as a DoD acquisition + design discipline: the statutory/regulatory basis (10 U.S.C. 4401–4403, FY2017/FY2021 NDAA, DFARS), the five OUSD(R&E) pillars, the plan→modularize→identify→define→standardize interface lifecycle, technical levers (WBS/MIL-STD-881F taxonomy, standards profiling, API-first software, COTS/cybersecurity), MOSA assessment metrics and tools (PART/OAAT/KOSS/SEAM/MAUT), technology-change and DMSMS management, roadmaps, MOSA across the six AAF pathways, and contracting/IP/data-rights mechanics. SCOPE LIMITS: this is U.S. DoD weapon-system acquisition policy, not a general open-architecture or interface-standards reference — it names standards (FACE, OMS, DISR) without reproducing them, is light on detailed engineering of any specific standard, and does not cover the underlying SE processes (use dau-se-guidebook / nasa-npr-7123) or general systems-engineering theory (use sebok).

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Use when working with Aws Systems Manager — aWS Systems Manager parameter store management, session management, patch compliance tracking, and Run Command analysis. Covers parameter inventory, managed instance status, automation execution, maintenance windows, and inventory collection.

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This skill should be used when the user asks to "escalate privileges on Linux", "find privesc vectors on Linux systems", "exploit sudo misconfigurations", "abuse SUID binaries", "exploit cron jobs for root access", "enumerate Linux systems for privilege escalation", or "gain root access from low-privilege shell". It provides comprehensive techniques for identifying and exploiting privilege escalation paths on Linux systems.

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This skill covers detecting cyber attacks targeting Supervisory Control and Data Acquisition (SCADA) systems including man-in-the-middle attacks on industrial protocols, unauthorized command injection into PLCs, HMI compromise, historian data manipulation, and denial-of-service against control system communications. It leverages OT-specific intrusion detection systems, industrial protocol anomaly detection, and process data analytics to identify attacks that traditional IT security tools miss.

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Analyze nonlinear dynamical systems — phase portraits, fixed points, stability analysis, bifurcation diagrams, Poincare sections, Lyapunov exponents, and chaos detection. Use for any autonomous or non-autonomous ODE system where qualitative behavior matters.

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Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)

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Expert firmware analyst specializing in embedded systems, IoT security, and hardware reverse engineering. Masters firmware extraction, analysis, and vulnerability research for routers, IoT devices, automotive systems, and industrial controllers. Use PROACTIVELY for firmware security audits, IoT penetration testing, or embedded systems research.

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This skill covers detecting cyber attacks targeting Supervisory Control and Data Acquisition (SCADA) systems including man-in-the-middle attacks on industrial protocols, unauthorized command injection into PLCs, HMI compromise, historian data manipulation, and denial-of-service against control system communications. It leverages OT-specific intrusion detection systems, industrial protocol anomaly detection, and process data analytics to identify attacks that traditional IT security tools miss.

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OpenClaw 전반의 품질을 지속적으로 검증합니다. 결함 재현부터 근본 원인 수정, 검토, 반영 확인까지 진행하고 실제 환경과 부하 검증 결과를 재개 가능한 보고서에 기록합니다.

• OpenClaw 여러 영역의 결함을 조사할 때
• 회귀 테스트와 독립 검토로 수정을 검증할 때
• 실제 연결, UI, 배포 패키지를 확인할 때

실시간 화면과 데이터 전달의 지연, 데이터 최신성, 처리 대기를 따로 측정합니다. 이벤트 발생부터 화면 표시까지 경로를 개선하고 운영 환경에서 결과를 확인합니다.

• 실시간 화면의 지연 조사
• 전달 데이터의 최신성 확인
• 대기열 적체 줄이기

문서·대화·프로젝트 정보를 알맞은 저장 위치로 정리합니다. 로컬 파일, 지식 기반, GitHub 등을 아우르며 중복 확인, 동기화, 검색을 진행합니다.

• 문서와 대화를 지식 기반에 저장
• 중복된 메모 정리
• 여러 저장 위치의 지식 동기화

Build HTML/CSS pages using visual specifications from 54 established websites, including Stripe, Linear, and Vercel. Templates provide colors, typography, spacing, component styles, and layouts that adapt to different screen sizes.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Creating a landing page inspired by Stripe
• Designing a dashboard inspired by Linear
• Styling a documentation website

기존 API와 기능의 폐기 판단부터 대체 구현으로의 단계적 이전, 사용 확인, 삭제까지 정리합니다. 운영 데이터베이스의 열 변경도 신구 코드가 공존하는 절차로 진행합니다.

• 기존 API에서 대체 API로 이전합니다
• 불필요한 기능의 종료를 계획합니다
• 운영 데이터베이스 열 이름을 단계적으로 바꿉니다

PR과 대규모 코드 변경을 자세히 검토해 설계 설명, 문제점, 병합 판단을 HTML이나 Markdown으로 정리합니다. 변경 차이뿐 아니라 시스템 전체의 동작도 확인합니다.

• 대규모 PR을 자세히 검토합니다
• 변경의 설계와 동작을 이해합니다
• 유사한 시스템과 설계를 비교합니다

GLSL로 유체, 입자, 규칙에 따라 생성되는 시각 효과를 제작합니다. 레이 마칭 등의 기법으로 페이지 첫 화면의 주요 이미지와 움직임을 포착한 정지 이미지를 만듭니다.

• 페이지 첫 화면의 주요 이미지 제작
• 유체 시뮬레이션 표현
• 입자 효과 제작

로고, 색상, 글꼴, 화면과 인쇄물의 적용 예시를 한 장의 이미지로 만듭니다. 브랜드의 목적과 대상에 맞춰 일관된 디자인 방향을 시각화합니다.

• 신제품의 브랜드 이미지 공유
• 의미가 담긴 로고 방향 검토
• 색상과 글꼴 및 적용 예시 확인

여러 AgentDB의 동기화와 관리, 의미 유사도와 속성 조건을 결합한 검색을 구현합니다. 검색 결과 중복 억제와 분산 AI 시스템 운영 설정도 다룹니다.

• 여러 AgentDB에서 기억 공유하기
• 의미 검색을 날짜나 분류로 좁히기
• 지식과 대화를 별도로 저장하기

AgentDB로 문서의 의미가 얼마나 가까운지에 따라 검색하는 기능을 구현합니다. 문서 저장, 유사도 검색, 속성 필터를 결합해 관련 자료를 참고하여 답하는 구조를 만듭니다.

• 검색한 자료를 근거로 답변 생성
• 지식 기반에 의미 검색 추가
• 내용이 비슷한 문서 찾기