“systems”的搜索结果

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 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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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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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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持续开展OpenClaw整体质量验证，从复现缺陷、修复根因到独立审查和确认合并，将真实环境及压力测试的证据和进度记录在可续接的报告中。

• 调查OpenClaw多个领域的缺陷
• 通过回归测试和独立审查验证修复
• 验证实际连接、界面及分发包

分别衡量实时界面与数据推送的延迟、数据新鲜度和待处理任务，梳理事件发生到屏幕显示的完整路径，逐段改进，并在运行环境中验证结果。

• 调查实时界面的延迟
• 检查推送数据的新鲜度
• 减少队列积压

将文档、会话和项目信息分类保存到合适的位置，跨本地文件、记忆工具、知识库和数据库查重、同步与检索，并维护索引和摘要。

• 将文档和会话保存到知识库
• 整理重复笔记
• 同步多个存储位置的知识

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.

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

从判断旧API或功能是否应停用，到分阶段迁移至替代方案、确认使用情况并删除旧实现，梳理完整流程。生产数据库的列变更也按新旧代码可共存的步骤推进。

• 从旧API迁移至替代API
• 制定不再需要的功能的停用计划
• 分阶段修改生产数据库列名

深入检查PR、分支或大规模代码变更，生成HTML或Markdown报告。除差异外，还梳理系统设计与运行方式，按重要程度列出问题，并提出是否合并及如何修改的建议。

• 深入审查大型PR
• 理解变更的设计与运行方式
• 与类似系统比较设计

使用GLSL制作流体、粒子及按规则生成的视觉效果，结合光线步进等技术，为页面首屏主视觉或捕捉动态瞬间的静态图提供制作支持。

• 制作页面首屏主视觉
• 探索流体模拟效果
• 制作粒子特效

将标志、配色、字体及屏幕和印刷品上的应用示例汇成一张品牌展示图，依据品牌目的与受众，呈现视觉风格统一的设计方案。

• 分享新产品的品牌形象
• 探讨具有明确含义的标志方案
• 集中查看配色、字体与应用示例

使用AgentDB实现按含义查找文档的搜索功能，将文档存储、相似度搜索与属性筛选结合起来，构建检索相关资料并据此回答问题的系统。

• 根据检索到的资料生成回答
• 为知识库添加语义搜索
• 查找内容相似的文档

实现多个AgentDB数据库的同步与管理，将语义相似度搜索与属性筛选结合，并配置搜索结果去重及分布式AI系统的运行方式。

• 在多个AgentDB数据库间共享记忆
• 按日期或分类筛选语义搜索结果
• 分别存储知识和对话

Analyze large matrices before solving linear systems. Check structure and numerical stability, recommend preprocessing and solver settings, estimate selected solution values without a full solve, and assess convergence, memory use, and computational cost.

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• Checking matrix properties before solving a system
• Choosing preprocessing for numerical stability
• Estimating selected values without solving the full system

Build document search with AgentDB that finds related content by meaning. Store documents as numerical representations, combine similarity search with metadata filters, and retrieve relevant passages for systems that generate answers using source material.

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• Build answers grounded in retrieved documents
• Add meaning-based search to a knowledge base
• Find documents with similar content

Build advanced AgentDB workflows with database synchronization, multiple databases, and search that combines meaning with attribute filters. Covers similarity measures, diverse search results, and operational patterns for distributed AI applications.

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• Sharing stored patterns across multiple AgentDB instances
• Filtering semantic search by date or category
• Separating knowledge and conversation databases