「ci」の検索結果

Comprehensive results analysis for empirical research: generate publication-quality descriptive statistics and balance tables, interpret regression coefficients with economic magnitude and effect sizes, assess identification assumption diagnostics, and produce structured results memos. Use when asked to create summary statistics, Table 1, balance tests, interpret results, assess economic significance, or write results narratives.

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Detects deeply nested loops with duplicated inline logic and recommends extracting into small, named functions. Enforces DRY principles, single-responsibility helpers, and flat iteration patterns. Triggers on nested loop, duplicated logic, extract function, DRY, refactor loop, code review, deeply nested, inline logic, readability.

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Interactive guided tour of all available AI coding skills with live demos. Walks through headline capabilities, offers try-it-now demos, discovers repo-specific tools, and provides a cheat sheet reference. Triggers on what can you do, show skills, skill tour, available tools, capabilities, what skills.

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Create authorized presenter, avatar, and UGC-style video drafts with explicit voice, likeness, consent, and synthetic-media handling.

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Apply a short artistic effect or VFX transformation to an approved media parent with explicit intent, provenance, and safety labeling.

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Plan and execute reference-driven movement using first/last frames, driving video, and model-specific motion controls.

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Create a non-explicit romantic scene from authorized adult references with clear consent, identity boundaries, and synthetic-media labeling.

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Turn an approved meme idea, image, or short source into a concise humorous video draft with a clear hook, caption plan, and platform variants.

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Knowledge base from NASA System Safety Handbook Volume 2 (NASA/SP-2014-612). Use for risk-informed safety cases (RISC), integrated safety analysis (ISA), adequate safety concepts, safety objectives and requirements, acquirer/provider roles, graded safety analysis, claims-evidence-argument structure, SSMP development, and RISC evaluation. Does not cover nuclear or chemical safety domains, occupational health regulations, or NASA-specific programmatic requirements beyond system safety.

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Knowledge base from NIST Secure Software Development Framework (SSDF) v1.1 (SP 800-218). Use for secure software development practices, SDLC security integration, software supply chain security, vulnerability disclosure, SBOM, threat modelling, secure coding, build hardening, EO 14028 compliance. Covers the four SSDF practice groups (PO, PS, PW, RV) only; does not cover NIST CSF, SP 800-53 controls, or cloud-specific security frameworks in depth.

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Guidance on writing high-quality requirements: the requirement quality characteristics and the EARS (Easy Approach to Requirements Syntax) patterns — ubiquitous, event-driven, state-driven, optional-feature, unwanted-behaviour — for unambiguous, singular, verifiable requirements, plus defect/anti-pattern review and verification & traceability. Use when authoring or reviewing requirements. Original synthesis citing EARS (Mavin et al.) and NASA public-domain guidance; not a reproduction of ISO/IEC/IEEE 29148 or the EARS paper.

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Knowledge base from NASA-STD-8719.14C (Process for Limiting Orbital Debris). Use for orbital-debris assessment planning, mission-related debris limits, explosion/passivation and collision risk, postmission disposal options, reentry casualty risk, and ODAR/EOMP governance. Covers STD-8719.14C (Approved 2021-11-05) synthesized notes only; does not replace NPR 8715.6 delivery timing, NASA-HDBK-8719.14 environment/modeling depth, or program-specific OSMA waivers.

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Knowledge base from the NIST/SEMATECH e-Handbook of Statistical Methods (NIST HB 151) — the practical statistics reference for engineering, metrology, and quality. Use for: exploratory data analysis and the four univariate assumptions (4-plot); measurement process characterization including bias/precision, calibration designs, gauge R&R, and ISO/GUM uncertainty budgets; production process characterization (stability vs. capability); process modeling and regression (LS/WLS/NLS/LOESS); design of experiments (screening, fractional/factorial, response-surface, Taguchi); statistical process control (Shewhart/CUSUM/EWMA charts, capability indices, acceptance sampling); product/process comparisons (hypothesis tests and confidence intervals for 1/2/3+ groups, ANOVA, multiple comparisons); and reliability (lifetime & repair-rate models, accelerated testing, reliability growth). Scope limits: this is applied frequentist statistics for measurement and quality — it does NOT reproduce the per-distribution formula galleries, worked case studies, datasets, plot images, or Dataplot/R code of the original web Handbook (those are described, not copied); it is thin on modern machine learning, Bayesian methods beyond conjugate reliability priors, time-series/forecasting, and Bayesian experimental design.

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Knowledge base from the GAO Agile Assessment Guide (GAO-24-105506, 2023). Use for assessing and managing Agile software development in federal programs: the Agile Manifesto and framework family (Scrum, Kanban, XP, SAFe, DA, DSDM, Lean, DevOps); the three adoption perspectives (team dynamics, program operations, organization environment); requirements decomposition (epics, features, user stories, INVEST, MoSCoW, definition of done); Agile-aware federal contracting (FAR, modular contracting, SOO/PWS/SOW, product owner vs. COR); program monitoring and control (WBS, cost, schedule, EVM at the feature level); Agile metrics (velocity, lead/cycle time, CFD, burn charts); and the auditor's key-question bank. Oversight- and acquisition-oriented: it tells you how to *assess and govern* Agile programs, not how to code. Thin on hands-on engineering practice, deep cost/schedule checklists (see gao-cost, gao-schedule), and any non-US-federal context.

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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 MIL-HDBK-516C (Airworthiness Certification Criteria). Use for DoD air-system airworthiness planning: tailoring a certification basis, systems engineering criteria, and domain clusters for structures, flight technology, propulsion/installation, avionics/electrical/E3/diagnostics, computer systems/software, and crew systems (including applicable UAS control-station elements). Qualitative guidance handbook — not raw contractual requirements. Does not replace service airworthiness authority policy, civil FAA certification rules as authorities, or detailed JSSG/MIL performance specs.

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Knowledge base from the GAO Technology Readiness Assessment Guide (GAO-20-48G, 2020). Use for evaluating technology maturity in acquisition programs and projects: Technology Readiness Levels (TRL 1–9) and related scales (MRL, IRL), identifying Critical Technology Elements (CTEs), the five-step process for a high-quality TRA, the four characteristics of a reliable TRA (comprehensive, well-documented, credible, defensible), Technology Maturation Plans (TMPs), and using TRA results in knowledge-based, milestone decisions. Assessment/maturity oriented: it measures readiness and frames risk — it is not a full SE process model, cost-estimating, or schedule guide (see sibling packs for those).

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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 the NASA Fault Management Handbook (NASA-HDBK-1002, Draft 2, April 2012). Use for the systems-engineering discipline of designing what a system does when it fails — the fault/failure/anomaly vocabulary, the five FM strategies (two prevention strategies — design-time fault avoidance and operational failure avoidance — plus three tolerance strategies — failure masking, failure recovery, and goal change), the six FM process activities across NASA mission phases Pre-A to E, response-latency-versus-time-to-criticality (TTC) design trades, fault/failure containment regions and FEPPs, the four redundancy approaches, top-down FM requirements development, FM verification vs. validation, the seven dedicated FM milestone reviews (FMCR/FMARR/FMPDR/FMCDR/FMTRR/FMLRR/FMCERR), FM organizational structure, and mined NASA Lessons Learned. Space-mission oriented (flight/ground/operations); spacecraft examples throughout. IMPORTANT: built from an UNAPPROVED DRAFT — several sections (detailed architecture building blocks, the Assessment & Analysis guidance, and Operations & Maintenance) are placeholders in the source and are thin here. Thin on detailed FDIR algorithms, terrestrial/IT fault management, and any approved-standard terminology that may have changed since Draft 2.

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Knowledge base from the DoD Test & Evaluation Enterprise Guidebook (OUSD R&E, August 2022). Use for DoD test and evaluation (T&E) across the Adaptive Acquisition Framework — the four test communities (contractor testing, developmental DT&E, operational OT&E, live-fire LFT&E); the five operational events (Operational Demonstration, EOA, OA, IOT&E, FOT&E) and the OTRR gate; the T&E Strategy / TEMP and its IDSK, with the upstream documents that feed it and the test plans that decompose it; the T&E organizations and oversight roles (USD(R&E), DOT&E, TRMC, the Service Executives and OTAs, the T&E WIPT, CDT); and pathway-specific T&E for all six acquisition pathways (Urgent Capability, Middle Tier, Major Capability, Software, Defense Business Systems). Statutory anchors include 10 U.S.C. §4171 (IOT&E) and §4172 (LFT&E/FUSL). This is guidance, not policy: it points outward to DoDI 5000.89 and the DoDI 5000-series for binding detail, and is thin on detailed test statistics/design-of-experiments methodology, cost estimating, the Acquisition of Services pathway, and any CUI/CAC-gated companion guides.

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Knowledge base from IS-GPS-200 Rev N (NAVSTAR GPS Space Segment / Navigation User Segment Interfaces). Use as a worked ICD/IS exemplar: what an interface specification is, DIST-A and IRN/CCB change control, interface definition vs identification, composite-signal criteria patterns, NAV data as payload families, and time/definition hygiene. Covers Rev N synthesized notes only; does not transcribe Apps II–IV bit fields or PRN/Gold-code tables, and does not replace faa-std-025 preparation rules.

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Knowledge base from NASA NPR 7123.1D — Systems Engineering Processes and Requirements. Use for the 17 common SE processes (SE Engine), life-cycle reviews and entrance/success criteria, SEMP structure and content, ETA roles and tailoring/customizing rules, Technology Readiness Levels (TRL 1–9), SE work product maturity terminology, contracted project oversight, and MOE/MOP/TPM measurement frameworks. Does not cover NASA programme financial management, human spaceflight medical standards, or software engineering requirements in depth (see NPR 7150.2 for the latter).

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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 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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