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Create and review company procedures and operational guides, then audit internal wikis for outdated pages, missing owners, broken connections, and inconsistent terminology. Produce structured drafts, step checks, and a prioritized list of documents to improve.
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Support stock and cryptocurrency analysis with reference formulas for price indicators, position sizing, and risk measures. The skill also covers financial data sources and Alpaca API operations, including market data retrieval, order management, and paper trading.
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Expert knowledge for Azure External Attack Surface Management development including configuration. Use when filtering EASM inventory by ASN, domains, hosts, IPs, pages, SSL certs, or exporting findings to analytics tools, and other Azure External Attack Surface Management related development tasks. Not for Azure Defender For Cloud (use azure-defender-for-cloud), Azure Security (use azure-security), Azure Sentinel (use azure-sentinel), Azure Networking (use azure-networking).
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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, VNet networking, Entra/OAuth auth, or AI/LLM backends, and other Azure API Management related development tasks. Not for Azure Functions (use azure-functions), Azure Logic Apps (use azure-logic-apps), Azure Service Bus (use azure-service-bus).
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Processes external resources into stored knowledge with quality scoring and routing. Use when ingesting articles, papers, or docs into a memory palace.
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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.
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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.
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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).
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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"
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Knowledge pack reconstructed from JSP 815 Defence Safety Management System V1.3 (Ministry of Defence, Open Government Licence v3.0): the SMS Framework, all 12 Elements with their Expectations and Performance Statement themes, and Annexes A to F plus H. Covers the Defence Safety Function and which JSP applies, leadership and safety culture, organisation and SEMS applicability, legislation and exemption certificates, risk assessment and safety cases, supervision and contracting, competence and letters of delegation, equipment and infrastructure safety, performance and incident management, and assurance, audit, and the ISO 45001 clause mapping. SCOPE LIMITS: single-source (JSP 815 V1.3 with Annex H V1.2); carries no DEF-STAN 00-051 or DEF-STAN 00-970 content, no JSP 375, JSP 816; acquisition safety policy is in jsp-376, no Annex G (Assurance Toolkit), and no ISO 45001 text (clause numbers only). This pack is reconstructed reference notes, not MOD guidance, and has no official status.
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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.
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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.
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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.
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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.
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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 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.
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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.
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Store useful patterns and solutions in AgentDB, then find them through semantic search, which matches meaning rather than exact wording. Use saved knowledge before starting work and record successful approaches and new lessons afterward.
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Combine tools for research, reference management, notes, document creation, and publishing. Agents check available software and credentials, then choose suitable tools based on output requirements, costs, and offline needs to build a complete workflow.
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Store project knowledge and design decisions in persistent memory that AI agents can search and read. New findings sync automatically to Markdown documentation, while usage statistics help you inspect the memory bank.
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Add social-emotional learning—practicing emotional awareness, self-management, empathy, and collaboration—to subject lessons in OpenMAIC. It connects these goals to academic concepts through discussion, choices, feedback, retries, and reflection.
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Helps build Angular v20+ applications with Signals, which track changing values, and self-contained Standalone Components. Covers state management, server rendering, performance improvements, and testing, including gradual updates to existing applications.
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Gives AI agents persistent project memory for architecture, implementation patterns, and decisions. Supports saving, searching, and retrieving knowledge, automatically syncing it with project documentation, and viewing memory usage through a dashboard.
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