「go」の検索結果

Knowledge base from the NASA Probabilistic Risk Assessment Procedures Guide (NASA/SP-2011-3421, 2nd ed.). Use for quantitative PRA of aerospace and safety-critical systems: the risk triplet and scenario logic stack (MLD, ESD, event trees, fault trees, minimal cut sets), Bayesian data collection and parameter estimation, aleatory/epistemic uncertainty modeling and common-cause failure (Alpha Factor, beta-factor, CCBE), human reliability analysis (THERP, CREAM, NARA, SPAR-H), context-based software risk (CSRM), physics-based and structural/phenomenological models (stress-strength, limit states, FORM/SORM, NASGRO, range safety), uncertainty propagation and importance measures (F-V, RAW, Birnbaum, DIM), and launch-abort modeling with worked PRA examples. This is the QUANTITATIVE engine beneath NASA's risk doctrine — for the qualitative RIDM/CRM decision framework use the nasa-risk pack. Thin on programme management, organisational risk governance, and non-aerospace regulatory contexts; aerospace-focused and anchored to the 2011 second edition.

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Knowledge base from EU Artificial Intelligence Act — Regulation (EU) 2024/1689. Use for AI system classification (high-risk vs prohibited vs general), conformity assessment procedures, GPAI model obligations, transparency and disclosure requirements, governance structure (AI Office / AI Board), penalty tiers, value-chain operator obligations, post-market monitoring, and Annex III use-case analysis. Does not cover EU liability rules for AI (separate proposed directive) or implementation guidance documents issued after July 2024.

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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 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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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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Use when the user asks to restate or explain the last message in plain, jargon-free language.

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Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.

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Layered technical-writing standard: Diátaxis structure, Google developer style sentences, STE instruction rules, Global English syntax. Use for /technical-writing or when writing or reviewing docs, RFCs, readmes, PR descriptions, or commit messages.

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Apply poteto's rigorous engineering workflow to non-trivial coding, investigation, review, migration, and verification tasks.

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Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions via show-me-your-work. Use for /figure-it-out, 'figure it out', a large migration, or when no narrower playbook applies.

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Structured problem solving in 6 steps: Problem definition, goals, brainstorming, evaluation, implementation, and review.

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Análisis de requisitos de documentos: Analiza los documentos de concepto y requisitos en la carpeta docs/, verifica los requisitos con el código actual y crea un informe de diferencias consolidado.

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Procedimiento estructurado de 6 pasos para mejorar, renovar o reconstruir pipelines existentes, carpetas de proyectos individuales, estructuras de documentación o stacks de software. Direccionable como "pipeline optimizer" (para pipelines temáticos completos, p. ej. de software, investigación o desarrollo de videojuegos) o "project-folder optimizer" (para carpetas de proyectos individuales dentro de un pipeline, p. ej. una herramienta de software o proyecto de artículo académico). Se activa ante tareas como "mejorar pipeline X", "optimizar el stack", "reconstruir Y", "renovación", "refactorización de pipeline", "limpiar carpeta de proyecto", "mejorar estructura de carpetas", "unificar convenciones", "consolidación de documentación", "integrar en sistema existente" o cualquier intervención sustancial en estructuras establecidas. Proporciona análisis del estado actual, aclaración del propósito, boceto del estado ideal, plan de brechas, identificación empírica de puntos de dolor y reevaluación con subagentes limpios. Previene estándares paralelos, duplicación y rupturas en el pipeline.

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Procedimiento estándar para la incorporación de nuevos proyectos de software: análisis de funciones, revisión de calidad de código, lista de verificación e integración de tareas.

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Canalización automatizada de desarrollo de software. Escanea proyectos, prioriza tareas, analiza código u orquesta bucles de desarrollo. Cero dependencias (solo la biblioteca estándar de Python).

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Ciclo de desarrollo de 8 fases: solicitudes de funciones, estado actual, planificación funcional, frontend, planificación de backend, código de backend, pruebas, casos de uso. Marco iterativo para el desarrollo sistemático de software.

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Barrido sistemático de errores con un valor objetivo escalado a la base de código, escalado por duplicación, seguimiento de áreas y verificación final. Se utiliza al ejecutar /bugsweep o cuando el usuario solicita una revisión sistemática de errores.

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Strukturiertes Problemlösen in 6 Schritten nach D'Zurilla und Goldfried: Problemdefinition, Ziele, Brainstorming, Bewertung, Umsetzung und Rückblick.

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Erweitert automation-self-care um Letter Hooks, Preflight-Bootloader, Dokument-Traversierungsregeln und selbstheilende Prompt-Kontext- Anreicherung für KI-Agenten und CLIs ohne native, ereignisgetriebene JSON-Lifecycle-Hooks (wie Antigravity / Gemini CLI). Nutzen, wenn ein Agent Preflight-Regeln injizieren, vor Arbeitsbeginn Memory/Gardener durchsuchen, Verzeichnis-Dokument-Lesestrategien erzwingen (CLAUDE.md / AGENTS.md) oder Sidecar-Tasks dynamisch an Skills und Sicherheitsprotokolle routen soll.

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Aktiver Finder/Router für die eigenen lokalen Skills (Analogon zu using-superpowers). IMMER zu Beginn einer nicht-trivialen Aufgabe nutzen, um zu prüfen, ob ein user-Skill passt, und zum richtigen Skill zu routen. Aktiviert sich bei „welcher Skill passt", „gibt es dafür einen Skill", „skill finden", oder generell vor Aufgaben, die ein lokaler Skill besser löst als ad-hoc-Arbeit.

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Erstellt oder überarbeitet einen Skill FÜR DIESES ÖKOSYSTEM: delegiert die generische Interview-/Entwurfs-/Eval-Schleife an das offizielle skill-creator-Plugin (Anthropic, Apache-2.0), setzt aber zusätzlich die ellmos-Anforderungen durch, die das offizielle Plugin nicht kennt — Haus-Frontmatter (9 Felder), Kategorie/Sichtbarkeits-Regeln, anbieter-/nutzer-/ellmos-neutrale aber ellmos-sensitive Erkennung via grounding-seed, mitgelieferte config.json (inkl. Lernvertrag) + connections.json, Anbieter-/Vendor-Bewusstsein (State-of-the-Art-Alternativen inkl. eigener ellmos-Komponenten vorschlagen), einen Selbstaktualisierungs-Abschnitt UND einen wiederverwendbaren Lern-/Abdeckungs-Dateisatz (user-usecases.json, usecase-gaps.json, known-providers-and-abilities.json, gap-closing-analysis.json — an skill-creators evals.json und A2A/AgentSkill angelehnt, kein Parallelstandard). IMMER nutzen, wenn ein NEUER Skill für dieses System entstehen oder ein bestehender auf ellmos-Konformität nachgerüstet werden soll — auch bei "erstelle einen Skill", "bau mir einen Skill für X", "skill-creator nutzen", "neuen Skill anlegen", "diesen Skill ellmos-konform machen", "Lernvertrag/Verhaltenscodex für einen Skill anlegen", "Usecase-Abdeckung eines Skills prüfen". Für reines Skill-FINDEN/ROUTEN stattdessen skill-finder, für Landschafts-Audit skill-explorer.

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Summarises one sprint from the board export, sprint report and review or stand-up notes the user provides into a one-page DRAFT sprint review summary: the sprint goal as written, items delivered, items not delivered with the reasons the sources state, carry-over, impediments, metrics exactly as given, and numbered questions for the retrospective, every row referenced to a work item or note fragment and every missing fact marked UNKNOWN. Use when the user asks to "summarise the sprint", "write the sprint review", "what did we deliver this sprint", "list the carry-over and blockers" or "draft the sprint recap". Do not use for the retrospective write-up or themed lessons across several sprints, use lessons-learned-synthesis instead; for a weekly project status report, use project-status-tracker. Drafts for human review; never approves, authorises or signs off.

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Turns a schedule extract (milestone list or planning tool export) and the period's status notes into a DRAFT plain-language slip explanation: which milestones and activities slipped and by how many working days, arithmetic shown, why per the notes as verbatim fragments with source and date, what each slip pushes next per the extract, and the decision each slip needs framed as a question with the options the notes propose and the owner the governance documents name, every missing fact marked UNKNOWN. Use when the user asks to "explain the schedule slip", "what slipped this month and why", "write the schedule commentary for the steering pack", "put the delay in plain language for the sponsor" or "what decisions do these slips need". Do not use for the weekly status report, use project-status-tracker instead; for cost variances, use budget-variance-explainer; for one sprint's carry-over, use sprint-review-summary. Drafts for human review; never approves, authorises or signs off.

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