「knowledge management」の検索結果

Expert knowledge for Azure API Management development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring APIM gateways, policies, VNets, self-hosted gateways, or AI/LLM-backed APIs, and other Azure API Management related development tasks. Not for Azure App Service (use azure-app-service), Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps), Azure Service Bus (use azure-service-bus).

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。

Expert knowledge for Cost Management development including troubleshooting, best practices, decision making, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing Azure budgets/alerts, cost exports, tags/views, billing APIs, or reservations/savings plans, and other Cost Management related development tasks. Not for Azure Advisor (use azure-advisor), Azure Monitor (use azure-monitor), Azure Quotas (use azure-quotas), Azure Policy (use azure-policy).

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。

Processes external resources into stored knowledge with quality scoring and routing. Use when ingesting articles, papers, or docs into a memory palace.

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。

Organizational strategy and management theory for business decision-making. Covers objectives-based management, the knowledge-worker firm, decentralization, the five management tasks, strategy-as-practice, managerial roles, and the distinction between efficiency and effectiveness. Use when structuring an organization, setting objectives, allocating decision rights, or critiquing a strategy document.

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。

Expert knowledge synthesizer specializing in extracting insights from multi-agent interactions, identifying patterns, and building collective intelligence. Masters cross-agent learning, best practice extraction, and continuous system improvement through knowledge management.

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 planning, sequencing, or troubleshooting an org-wide migration from Salesforce Classic to Lightning Experience. Covers the LEX Transition Assistant Readiness Check, asset triage matrix (Visualforce, JavaScript buttons, page layouts, Knowledge, email templates, list views, AppExchange), pilot/wave rollout sequencing, end-user adoption telemetry, and cutover criteria. Triggers: 'lightning experience transition', 'classic to lightning migration plan', 'LEX readiness check', 'why are some users still on Classic', 'turning on Lightning for everyone'. NOT for individual asset migrations like a single VF page (use lwc/visualforce-to-lwc-migration), a single JavaScript button (use admin/custom-button-to-action-migration), or Knowledge article migration (use admin/knowledge-classic-to-lightning) — this skill orchestrates the program. NOT for Lightning App Builder page design (use admin/lightning-app-builder-advanced).

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。

DAMA-DMBOK（Data Management Body of Knowledge）準拠のデータマネジメントスキル。 11の知識領域（データガバナンス、データ品質、メタデータ管理、MDM等）を網羅し、 データ戦略策定から具体的な改善施策まで支援する。 Use when: データ戦略策定、データガバナンス構築、データ品質改善、データカタログ作成、 MDM導入、DX推進、データ移行プロジェクト、データ成熟度評価。 Triggers: "データガバナンス", "データ品質", "データカタログ", "メタデータ管理", "MDM", "データ戦略", "DMBOK", "データ成熟度", "データリネージ"

Knowledge base from NIST SP 800-37 Revision 2, the Risk Management Framework (RMF) for information systems and organizations. Use for the seven RMF steps (Prepare, Categorize, Select, Implement, Assess, Authorize, Monitor) and their tasks; the three-tier organization-wide risk model; authorization boundaries; the requirements-to-controls relationship; security categorization (FIPS 199/200 high-water mark) and control selection/tailoring (SP 800-53/53B baselines); assessment, the authorization decision and risk acceptance, continuous monitoring and ongoing authorization; the security/privacy distinction; and supply chain risk management. This is the security-and-privacy-risk-governance edge of systems engineering — it governs how much protection and whether to accept residual risk, complementing the disciplines that decide how protection is built. Does NOT reproduce the SP 800-53 control catalog or its baselines, the FIPS impact tables, or the ISO/IEC/IEEE 15288 process text; it names and routes to them rather than restating them.

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Knowledge base from NIST Cybersecurity Framework (CSF) 2.0. Use for cybersecurity risk management, GOVERN, IDENTIFY, PROTECT, DETECT, RESPOND, RECOVER, Organizational Profiles, CSF Tiers, supply chain risk, enterprise risk management, incident response. Covers the CSF 2.0 document only; does not cover specific SP 800-53 controls, NIST RMF system authorization steps, or sector-specific regulations.

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 Schedule Assessment Guide (GAO-16-89G, 2015). Use for building, assessing, or auditing a program's integrated master schedule (IMS): the ten best practices of a reliable schedule (capture, sequence, resource, duration, traceability, valid critical path, reasonable total float, schedule risk analysis, updating, baseline), the four characteristics (comprehensive, well-constructed, credible, controlled), critical path method arithmetic (forward/backward pass, total float), schedule risk analysis (Monte Carlo, contingency), statusing and baseline control, and the Appendix II audit triad. Scheduling/time-management oriented: it is the authority on schedule reliability, but it is NOT a cost-estimating guide, a full SE process model, an agile guide, or a risk-management framework — see sibling packs (gao-cost, dau-se-guidebook, nasa-schedule, nasa-risk) for those.

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 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.

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 FAA-HDBK-006D (2020), the FAA's System Reliability, Maintainability, and Availability (RMA) Handbook for National Airspace System (NAS) hardware and software. Use for RMA figures of merit (MTBF, MTBO, MTTR, the availability variants), the bathtub curve and probability distributions, the four-stage RMA lifecycle mapped to the FAA Acquisition Management System (AMS), the six-task RMA technical-management/acquisition process, service-thread criticality and the NAS-RD severity-to-target table, the RMA analysis toolbox (RBD, FMEA/FMECA, FTA, Ishikawa, Monte Carlo, Bayesian, FRACAS, ALT, reliability-growth/recovery tests), software reliability (early prediction + reliability growth), and tailorable example RMA requirements for a Program Requirements Document. Scope limits: it is FAA/NAS-specific guidance (not a requirement, by its own statement), centred on hardware-plus-software availability — it brackets out human/service/facility/communications availability, names but does not reproduce the math derivations or external standards (MIL-STDs, IEEE 1633, RTCA DO-178C/DO-278A, SAE JA1011), is thin on detailed worked numerical examples and on safety-case method, and predates any current revision beyond 006D.

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 NASA Risk Management Handbook (NASA/SP-2011-3422). Use for risk-informed decision making, continuous risk management, performance commitments, risk scenario diagrams, risk disposition types, risk burn-down schedules, objectives hierarchies, deliberation and alternative selection, risk driver identification, and RM planning for space and safety-critical programmes. Does not cover domain-specific PRA methods (fault trees, event trees) in procedural depth — see NASA PRA Procedures Guide for those.

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 DoD Systems Engineering Guidebook (OUSD R&E, February 2022). Use for the DoD SE process model — the 16 SE processes (8 technical management + 8 technical) mapped to ISO/IEC/IEEE 15288, the event-driven technical reviews and audits across the Major Capability Acquisition life cycle (ASR, SRR, SFR, PDR, CDR, SVR/FCA, PRR, PCA), the Systems Engineering Plan (SEP), risk/issue/opportunity management, TPMs and leading indicators, system-of-systems and digital engineering, and the 24 design considerations (RAM, system safety, HSI, system security engineering, MOSA, supportability, etc.). Acquisition-program oriented: thin on detailed cost estimating, contracting law, and non-DoD or commercial life cycles.

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 FAA AMS Lifecycle V&V Guidelines (verification and validation), Version 3.0, dated April 2017. Use for applying verification and validation across the FAA Acquisition Management System (AMS) lifecycle: the verify-vs-validate distinction (built right vs. right thing), the work-product/component/product tiers, the nine V&V planning elements, the four method catalogs (Appendix C), decision-point-gated V&V (SASP, CRD, Investment Analysis, Solution Implementation, In-Service Management), the Appendix B document checklists (PRD/APB/ISPD/PMP), and the DT/OT/IOA test triad. Scope limits: this is an FAA acquisition-V&V doctrine, NOT a general SE process model, requirements-engineering manual, or test-design textbook. It borrows its core V&V definitions from CMMI v1.2 (SEI, paraphrased) and presumes the surrounding AMS lifecycle (see the FAA SEM pack); its phase tables are policy snapshots as of April 2017 and it is thin on detailed test methods, tool specifics, and anything outside FAA acquisition governance.

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。

Two-tier memory system that makes Claude a true workplace collaborator. Decodes shorthand, acronyms, nicknames, and internal language so Claude understands requests like a colleague would. CLAUDE.md for working memory, memory/ directory for the full knowledge base.

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Simple task management using a shared TASKS.md file. Reference this when the user asks about their tasks, wants to add/complete tasks, or needs help tracking commitments.

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。

Expert knowledge for autonomous market intelligence and trading — technical analysis, risk management, Alpaca API, financial data sources

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。

Builds AI agents on Cloudflare using the Agents SDK with state management, real-time WebSockets, scheduled tasks, tool integration, and chat capabilities. Generates production-ready agent code deployed to Workers. Use when: user wants to "build an agent", "AI agent", "chat agent", "stateful agent", mentions "Agents SDK", needs "real-time AI", "WebSocket AI", or asks about agent "state management", "scheduled tasks", or "tool calling". Biases towards retrieval from Cloudflare docs over pre-trained knowledge.

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。

Capture, validate, query, and sync architectural patterns and design decisions in the knowledge graph

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。

管理本地 Markdown/Obsidian 知识库：素材入库、健康检查、增量索引、关键词与 semantic-lite 检索、逐字原文资料包、归档和 MCP 连接。用于搜索知识库、整理资料及为 Agent 准备可定位的引用。

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。

Expert knowledge for Azure Quotas development including limits & quotas. Use when requesting per-region Storage account quota increases, checking limits, or filing Azure support requests, and other Azure Quotas related development tasks. Not for Azure Cost Management (use azure-cost-management), Azure Monitor (use azure-monitor), Azure Policy (use azure-policy), Azure Resource Manager (use azure-resource-manager).

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Expert knowledge for Azure Resource Graph development including troubleshooting, best practices, decision making, limits & quotas, configuration, and integrations & coding patterns. Use when querying via CLI/PowerShell/REST, using GET/LIST vs Query, handling paging/quotas, or Power BI ARG reports, and other Azure Resource Graph related development tasks. Not for Azure Monitor (use azure-monitor), Azure Policy (use azure-policy), Cost Management (use azure-cost-management), Azure Resource Manager (use azure-resource-manager).

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。

Expert knowledge for Azure Sentinel development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring data connectors, KQL analytics rules, Logic Apps playbooks, data lake jobs, or SAP integration, and other Azure Sentinel related development tasks. Not for Azure Defender For Cloud (use azure-defender-for-cloud), Azure Security (use azure-security), Azure Monitor (use azure-monitor), Azure External Attack Surface Management (use azure-external-attack-surface-management).

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。