「gold」の検索結果

Design and implement unit, conformance, integration, timing, boot, trace, video, audio, and regression tests for EMULATORS processors, chips, peripherals, and complete machines. Use when creating a verification strategy for a new emulator, converting hardware documentation into tests, adding diagnostic programs or golden artifacts, measuring behavioral coverage, or proving that components interact correctly.

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FOUNDATIONAL SKILL - Analyze every prompt for underlying motivation using Golden Circle (WHY->HOW->WHAT). Runs BEFORE any other skill. No action without understanding WHY.

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This skill should be used when the user asks to "attack Active Directory", "exploit AD", "Kerberoasting", "DCSync", "pass-the-hash", "BloodHound enumeration", "Golden Ticket", "Silver Ticket", "AS-REP roasting", "NTLM relay", or needs guidance on Windows domain penetration testing.

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

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Open the alpha review screen to mark judge keepers as gold or miss, read per-miner precision, and print the eval state. Use when tuning a miner's accuracy. Thin launcher over the existing harvest engine and local review server. Triggers: "/alpha-review", "alpha screen", "open the review screen".

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Operational guide for the NV oOS Dictation desktop companion app (Tauri v2 + Rust, examples/nvoos-dictate) — build/run on Windows/MSVC, the local-first engine track (parakeet/whisper/moonshine/silero-vad, all API-verified against pinned crate versions), the embedded remote-STT fallback against the Embedded addon's transcribe route, model registry + verification harnesses, the plugins.updater boot-crash config rule, and the full test/clippy gate matrix. Use when building, extending, or debugging the dictation app, adding an engine or model, touching the cleanup pipeline golden tests, or continuing the P2/P4/P5/distribution follow-up work.

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Prompt engineering regression test matrix register: baseline outputs, semantic drift thresholds, judge evaluations, and golden dataset.

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Build automated evaluation suites for AI agents using golden datasets, rubrics, and regression gates. Use when shipping agent features, validating prompt changes, or gating deployments on quality.

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Expert-level guidance for Flutter production applications: architecture decisions (Clean/Layered/Hexagonal/Feature-First), advanced state management (BLoC/Riverpod/GetX), performance optimization (eliminating jank, memory profiling, reducing rebuild overhead), code review with design pattern enforcement, scalability assessments, native platform integration (MethodChannel/EventChannel/FFI), complex UI challenges (custom render objects, slivers), testing strategies (unit/widget/integration/golden), CI/CD pipeline architecture, build optimization, and accessibility compliance. Triggers: 'architecture decision', 'design pattern', 'performance issue', 'code review', 'production problem', 'scaling concerns', 'best practices', 'technical debt', 'refactoring strategy'. Essential for complex enterprise apps, critical production debugging, architectural refactors, or when choosing between competing technical approaches.

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This skill should be used when the user asks to "attack Active Directory", "exploit AD", "Kerberoasting", "DCSync", "pass-the-hash", "BloodHound enumeration", "Golden Ticket", ...

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Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the Alpha Vantage API. Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Requires a free API key from alphavantage.co.

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Improve AI application with evaluation-driven development. Define eval criteria, instrument the application, build golden datasets, observe and evaluate application runs, analyze results, and produce a concrete action plan for improvements. ALWAYS USE THIS SKILL when the user asks to set up QA, add tests, add evals, evaluate, benchmark, fix wrong behaviors, improve quality, or do quality assurance for any Python project that calls an LLM model.

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。

This skill should be used when the user asks to "attack Active Directory", "exploit AD", "Kerberoasting", "DCSync", "pass-the-hash", "BloodHound enumeration", "Golden Ticket", "Silver Ticket", "AS-REP roasting", "NTLM relay", or needs guidance on Windows domain penetration testing.

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Use after the Lean model changed and before touching backend code — regenerates Kotlin from Lean, lists changed generated symbols, the hand-written files and contract tests that reference them, and golden regressions, so the blast radius is known before implementation.

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Use when you need the current position in the Lean spec-driven pipeline, or any deterministic check of a Cradle project — status, golden regression, Lean layer walls, regeneration impact, unslop lint, ddd cleanup. Runs the scripts under scripts/ and reports their output verbatim.

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Use to create, update or run the spec-animation mockup under lean/mockup — "run the mockup", "show the model on a screen", "try this scenario", "demo for the expert", "save a golden" — and to build the domain-language screens that let the expert review the model without reading JSON. The mockup executes the Lean model as-is; no logic in JS.

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Use after the backend follows the model — derive E2E flow scripts from Lean golden traces, replay them against the Lean-backed dev screens and the real REST backend with Playwright, and compare observations. Also use to add a flow when a new command or screen appeared.

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Diagnostic test / biomarker accuracy — sensitivity, specificity, PPV, NPV, likelihood ratios, accuracy from a 2x2 table; ROC curve, AUC, and the optimal cutoff (Youden) for a continuous biomarker; and post-test probability via Bayes. Use when you have test results vs a gold standard (binary 2x2, or a continuous score + true labels) and need to judge how good the test is, pick a threshold, or compute the probability of disease given a result. Emphasizes the prevalence-dependence of PPV/NPV.

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Designs covalent inhibitors and warheads targeting cysteine (most common, 98% of covalent drugs), lysine, serine, threonine, tyrosine, and aspartate residues, with explicit handling of warhead reactivity (acrylamide, chloroacetamide, vinyl sulfone, sulfonyl fluoride, fluorosulfate, aldehyde, boronate, nitrile), reversibility (kinact/Ki, t_residence), glutathione (GSH) stability, intrinsic reactivity assays, and covalent docking (DOCKovalent, GOLD, HCovDock). Use when designing covalent inhibitors for targeted covalent inhibition (TCI), KRAS G12C-style approaches, or rationalizing covalent SAR.

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Predicts ADMET properties using ADMETlab 3.0 (119 endpoints with uncertainty), ADMET-AI, DeepChem MolNet, and chemprop D-MPNN with explicit handling of OECD QSAR principles, applicability domain assessment, calibration, hERG/CYP/AMES gold-standard endpoints, and PAINS / Lipinski / Ro5 / Veber / BBB druglikeness filters. Use when filtering compounds for drug-likeness, prioritizing leads by predicted safety, or building an in-house ADMET QSAR model.

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Integrate Red Hat Ansible Automation Platform (AAP) with HashiCorp Vault Enterprise for dynamic SSH credential management. Use when: (1) Configuring Vault SSH secrets engine with AppRole auth for AAP, (2) Creating AAP credentials backed by Vault signed SSH certificates, (3) Provisioning infrastructure with Terraform/Ansible for AAP-Vault integration, (4) Setting up multi-tenant credential management, (5) Configuring golden images to trust Vault SSH CA, (6) Implementing credential rotation strategies. Based on HashiCorp validated pattern.

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Infer gene regulatory networks from bulk or general expression data with mutual-information (ARACNe) and tree-ensemble (GENIE3, GRNBoost2) methods, and infer transcription-factor protein activity from regulons with VIPER and msVIPER. Covers the activity-not-edges paradigm, the undirected-association caveat, the DREAM5 wisdom-of-crowds and method-complementarity result, AUPRC-over-AUROC evaluation, and gold-standard incompleteness. Use when inferring a regulatory network from a bulk expression matrix, finding master regulators, or scoring TF activity from a signature. For single-cell motif-pruned regulons see scenic-regulons; for co-expression modules see coexpression-networks.

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Visualize biological networks (PPI, gene-regulatory, co-expression, pathway) with layout algorithm choice (ForceAtlas2, Fruchterman-Reingold, Kamada-Kawai, hive plots), edge bundling, community-based coloring, and reproducible seeds using NetworkX, PyVis, igraph, and Cytoscape automation. Use when rendering biological networks for static publication, interactive HTML exploration, or Cytoscape-format export.

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。