「production」の検索結果

Author and submit a Narrative workflow from a natural-language intent. Picks the closest example from `assets/examples/`, adapts it to the user's case, walks the YAML against the spec, resolves the data plane, and submits via `narrative_workflows_create` only after the user has approved the rendered spec. Use when: "create a workflow that does X", "schedule a daily refresh of dataset Y", "wrap this NQL as a workflow", "build a pipeline that creates view A then refreshes view B", "submit this workflow YAML", "productionize this query as a recurring job". (narrative-common)

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Investigate latency, freezes, memory growth, hitches, dropped frames, or perceived slowness with reproduction and instrumentation before optimizing.

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Load for .NET observability changes involving structured logs/Loki, Prometheus metrics, OpenTelemetry traces, exception handling, correlation IDs, dashboards, alerts, or production error diagnosis; not for ordinary business validation errors.

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Throwaway design probe for logic, state models, UI variations, and affordances before production work. Use when the user wants to prototype, sanity-check a model, make something playable, compare UI directions, or explore a design before ln-spec/ln-plan/ln-scope.

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Time-boxed throwaway investigation to answer one hard question. Use when facing technical uncertainty before committing to a frontier item or scoped slice — the output is knowledge, not production code.

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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 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 DoD M&Q BoK (the Manufacturing and Quality Engineering Body of Knowledge), v3.0 of July 2025, published by OUSD(R&E). Use for the manufacturing-and-quality view of the defense acquisition life cycle: what M&Q engineers do across the Adaptive Acquisition Framework phases (Pre-MDD, Materiel Solution Analysis, Technology Maturation and Risk Reduction, Engineering and Manufacturing Development, Production and Deployment, Operations and Support); the twelve M&Q threads (A–L) built on the '5 Ms'; manufacturing feasibility and producibility; Manufacturing Readiness Levels and assessments; Key/Critical Characteristics and process capability (Cp/Cpk, SPC); the standards stack (AS6500, AS9100/ISO 9001, AS9103, AS9145); technical reviews (ASR/PDR/CDR/PRR) and milestone gates; DCMA surveillance; industrial base and supply chain; and sustainment (LCSP, IPS, ILA, ISR). Scope is DoD acquisition M&Q practice on the Major Capability Acquisition path — it is a best-practice compilation, not policy, and is thin on detailed shop-floor process engineering, contract law, and the full text of the cited industry standards (which it names but does not reproduce).

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KI-gestuetzte Textproduktion in drei Teilskills: Allgemeine Texte (Blogpost, Social, Newsletter, Copy, E-Mail, Bericht), narrative Storys (Skript, Kurzgeschichte, RPG, Weltenbau) und PR-Kommunikation (Pressemitteilung, Positionspapier) mit lokalem LaTeX-PDF-Compiler. Kein externer Dienst zwingend erforderlich.

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Query Sentry issues, events, releases, replays, and org/project metadata via REST API. Use when the user wants to diagnose a production error, pull stack traces, list recent issues, inspect a release, or fetch event data programmatically — prefer this over asking for UI screenshots or guessing from memory.

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Takes existing content markdown files and builds production-final resource center pages on client websites using their existing tech stack and design system. Output is live-ready — no review pass, no placeholder content, no prototype styling. Implements hub pages, section listings, article pages, and cross-linking for Blog, Guides, Learn, and Comparisons sections.

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Merge dev branch into master/main and push. Use when dev changes are ready for production branch. Invoked by saying "merge to master" or "merge to main".

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Deployless delivery-model audit. Use first when adapting any repository toward single-mainline development, automatic deployment from main, runtime release controls, production-trace-driven iteration, AI PR governance, or multi-agent delivery workflows.

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Use when converting a design direction into maintainable production frontend code, selecting architecture within the existing stack, implementing semantics, assets, loading behavior, CSS/layout, components, and progressive enhancement.

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Per-toolkit hardening audit loop for NV oOS Pro tools. Systematically scans each addons/pro/includes/tools/<toolkit> (and its plugins/nvoos-content-graph-pro mirror) for the four recurring production failure classes — unguarded shell calls that fatal on exec-disabled hosts, calls to nonexistent client methods, string-assuming parsing of provider responses that may be arrays, and provider enum/service mismatches — then fixes, tests (Docker PHPUnit), and validates (phpcs both standards) before moving to the next toolkit. Use when asked to audit a toolkit, review the X tools for similar issues, do the same for the other toolkits, or continue the toolkit audit loop. The first case study (document-generation) found 3 fatal bugs + 1 broken regex.

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Repair and triage guide for the NV oOS PHPUnit test suite — Docker test environment (incl. cross-worktree one-off runners), CI log triage, and 71 recurring root-cause patterns (hook resets, singleton interference, WP_Error envelope drift, coverage-manifest drift, preset-accounting gaps, and more — see the patterns section). Covers the cluster-by-cluster PR workflow against alpha-working and validation gates. Use when fixing failing PHPUnit tests, triaging CI logs, repairing test drift, deciding between a production fix and a test fix, or starting a new fix cluster.

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Audits WordPress plugin/theme code for secret-handling and credential issues — hardcoded API keys, DB credentials, or signing secrets in source; weak randomness (rand, mt_rand, uniqid) used for security tokens, password reset links, nonces, or session IDs; password storage with md5/sha1/crypt instead of password_hash; insecure cookie flags (missing Secure, HttpOnly, SameSite) on sensitive cookies; secrets logged via error_log / var_dump in production code paths. Use before plugin release, when reviewing auth/registration/login features, when integrating third-party APIs, or when the user mentions "API key", "token", "session", "password reset".

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Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications (examples include websites, landing pages, dashboards, React components, HTML/CSS layouts, or when styling/beautifying any web UI). Generates creative, polished code and UI design that avoids generic AI aesthetics.

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Generate production-quality Excalidraw architecture diagrams from natural language. Visual structure maps to conceptual structure — fan-out for one-to-many, timelines for sequences, convergence for aggregation. Includes self-validation via Playwright render review.

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Design and execute DAG-based automation workflows using the NV oOS Pro Workflow Builder — a ReactFlow visual builder for chaining tool calls, agent runs, and actions into repeatable pipelines. Covers the visual builder UI, 10 preset categories (incl. AI Fashion Production, v1.1.92+), 10 node types, Kahn's algorithm execution engine, scheduling via Pro Schedule Manager, template variable syntax, and best practices. Use when designing workflows, debugging DAG execution failures, choosing between a workflow schedule and raw tool chaining, or building CRM/PM automation pipelines with toolkit_cpt nodes.

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Generates production-grade Appium mobile automation scripts for Android and iOS in Java, Python, or JavaScript. Supports real device and emulator testing locally and on TestMu AI cloud with 100+ real

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Builds production-ready REST API endpoints with validation, error handling, authentication, and documentation. Follows best practices for security and scalability.

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Generates complete, production-ready REST API endpoint specifications for any system or domain the user describes.

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Production-grade Android app development guide covering native (Kotlin/Java), cross-platform (Flutter, RN, KMM), and hybrid architectures.

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。