「cv」の検索結果

Use when the user asks to "is my ad fatiguing", "why is CTR dropping at scale", or "should I rotate creative / widen the audience"; reads frequency, CTR and CVR decay against an early-flight baseline and returns Rotate-creative / Widen-audience / Hold triggers with a per-ad-set fatigue read. Not for building the replacement creative — use ad-creative-builder; not for the RQS score or vetoes — use ad-account-auditor. 广告疲劳检测/频次管理/换素材还是扩人群

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Implements Riverpod (v3.3.x) compile-safe state management for Flutter apps. Use when implementing @riverpod code generation providers, handling AsyncValue loading/error/data states, using ref.watch/ref.read/ref.listen, setting up ProviderScope, writing Notifier/AsyncNotifier classes, using FutureProvider/StreamProvider, applying autoDispose and family modifiers, combining providers, testing providers in isolation, scoping rebuilds with Consumer instead of ConsumerWidget, using ref.watch with select() for field-level precision, migrating from StateNotifierProvider or Riverpod 2.x patterns, handling Notifier resource lifecycle with ref.onDispose, or using experimental Mutation and offline persistence APIs.

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CVE vulnerability lookup via NIST NVD, CISA KEV, EPSS scores, and MITRE ATT&CK. 7 tools for real-time cybersecurity intelligence.

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Use Kanpeki component library in React projects. Activate when user wants to add, use, customize, or compose accessible UI components from Kanpeki (@kanpeki/*). Covers installation, component patterns, forms, theming, and dark mode with React Aria Components + Tailwind CSS 4.1 + CVA.

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Use for pip CVE scanning and auto-patching via OSV.dev API.

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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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Data scientist v3 — ML, deep learning, NLP, CV, experimentation, MLOps

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Calculate portfolio risk metrics including VaR, CVaR, Sharpe, Sortino, and drawdown analysis. Use when measuring portfolio risk, implementing risk limits, or building risk monitoring systems.

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Monitor social platforms for security threats, vulnerability discussions, and breach intelligence using Xpoz. Use when asked to "find CVE discussions", "security threat monitoring", "OSINT social media", "vulnerability intelligence", "breach mentions", or "threat intel from Twitter/Reddit".

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Use when evaluating, critiquing, transforming, or generating a Master's Informatics thesis idea, research gap, novelty, research question, experiment, AI/ML/CV/NLP/LLM/Edge-AI method, or when distinguishing R&D research from software implementation using the Frascati Manual 2015.

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面试复盘 skill（求职者视角）。把一次已结束的面试，从「文字记录」沉淀成结构化复盘：逐题诊断 + 5 维评分 + 更优回答范本 + 下一场准备清单，最终产出一份飞书复盘文档。当用户说"面试复盘"、"复盘一下面试"、"刚面完 XX 帮我盘下"、"这场面试哪答崩了"、"面试问答记录帮我分析"时触发。区别于 resume-optimizer / cv-expert（面试前优化简历），本 skill 处理「面完之后」。

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This skill should be used when the user asks to "优化简历", "resume optimization", "简历诊断", "tailor resume to JD", "改简历", "resume review", "简历优化助手", or when the user mentions "校招", "社招", "ATS", "JD匹配", "Word批注", shares a .docx resume path alongside a job description, or wants to match their resume to a specific job posting. Also triggers on "resume expert", "HR feedback", "interview prep with resume".

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AI-powered E2E web testing — eyes and hands for AI coding tools. Declarative YAML scenarios, Playwright execution, visual matching (OpenCV + OCR), platform auto-detection (Flutter/React/Vue), learning DB. Install: npx skills add ksgisang/awt-skill --skill awt -g

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tespit etme (s) container escape attempts by analyzing namespace configurations, privileged container checks, dangerous capability assignments, and host path mounts using the kubernetes Python client. Identifies CVE-2022-0492 style escapes via cgroup abuse. Use auditing yaparken container security posture or investigating escape attempts.

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JWT saldırıları — alg:none, HMAC brute-force, floating point bypass, CVE-2022-39227

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Provides cryptography attack techniques for CTF challenges. Use when attacking encryption, hashing, signatures, ZKP, PRNG, or mathematical crypto problems involving RSA, AES, ECC, lattices, LWE, CVP, number theory, Coppersmith, Pollard, Wiener, padding oracle, GCM, key derivation

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End-to-end ABM program design and orchestration for B2B SaaS mid-market and enterprise motions. Use when building a target account list, designing account tiering criteria, planning ABM channel orchestration, coordinating BDR outreach with marketing campaigns, defining ABM measurement frameworks, or running an ABM program review. Also use when asked to "build an ABM program," "set up account-based marketing," "design a target account strategy," "plan ABM campaigns," or "measure ABM results." Designed for demand gen teams selling to Mid-Market companies with $10K-$50K+ ACV, multi-persona buying committees, and 3-6 month sales cycles.

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Builds a structured vulnerability scanning workflow using tools like Nessus, Qualys, and OpenVAS to discover, prioritize, and track remediation of security vulnerabilities across infrastructure. Use when SOC teams need to establish recurring vulnerability assessment processes, integrate scan results with SIEM alerting, and build remediation tracking dashboards.

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Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.

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Validates predictive models on omics and biomedical data with nested cross-validation, group/batch/temporal-aware splits, the full data-leakage taxonomy, probability calibration, decision-curve net benefit, optimism correction, sample-size planning, and TRIPOD+AI reporting. Use when estimating model performance honestly, choosing a CV scheme, detecting leakage, or judging whether reported discrimination means the model is actually useful. For feature selection itself see machine-learning/biomarker-discovery; for confirmatory-trial inference see clinical-biostatistics/trial-reporting.

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Maps query single-cell data onto reference atlases and transfers cell-type labels using scArches surgery (scVI/scANVI), Symphony, Azimuth, CellTypist, scPoli, popV, and foundation models, with explicit out-of-distribution and label-transfer uncertainty. Use when annotating new single-cell datasets against a pre-trained reference, deciding which mapping method fits, or judging whether transferred labels are trustworthy. For de novo clustering and manual annotation see single-cell/cell-annotation; for batch integration without a reference see single-cell/batch-integration.

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Programmatic untargeted LC-MS feature extraction in R with the modern xcms 4.x MsExperiment/XcmsExperiment API, taking raw mzML to a feature table via CentWave peak detection, retention-time alignment, peak-density correspondence, gap-filling, CAMERA redundancy collapse, and built-in QC feature filtering. Use when converting centroided LC-MS runs into a features-by-samples matrix and deciding centWave/grouping/alignment parameters. For drift correction and QC/CV filtering execution see metabolomics/normalization-qc; for metabolite identification see metabolomics/metabolite-annotation; for the MS-DIAL GUI alternative with MS2Dec deconvolution see metabolomics/msdial-preprocessing; for downstream statistics see metabolomics/statistical-analysis.

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Computes and interprets sequencing read depth and coverage over a genome, windows, or target regions with mosdepth (windowed depth, cumulative distribution, --quantize callable BEDs), bedtools genomecov/coverage (bedGraph tracks, per-target stats), samtools depth/coverage (per-base depth, per-contig depth+breadth). Covers the breadth-vs-mean distinction, the cumulative-coverage curve, evenness (CV/Fano/fold-80/Gini), what each tool silently counts (duplicates, secondary/supplementary, MAPQ, read span vs fragment, mate-overlap), the samtools-depth 8000-cap version trap, and the bedtools coverage -a/-b orientation flip. Use when assessing sequencing adequacy, building coverage tracks, computing breadth at a depth threshold, defining callable regions, or QCing target-capture uniformity.

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Creates DE-specific diagnostic and result visualizations using DESeq2/edgeR built-in functions and lightweight ggplot2 wrappers. Covers MA plot (with the shrunken-LFC compression effect), volcano (with the apeglm caveat that p-values are unchanged), PCA on VST/rlog (never raw counts), sample distance heatmaps, top-DE-gene heatmaps with the row-scaling trap, dispersion / BCV plot interpretation, p-value histogram diagnostics, plotCounts for individual genes, blind=TRUE vs FALSE rationale, and the n=3 visualization stake. Use when generating DE diagnostic plots, choosing VST vs rlog for visualization, troubleshooting suspicious plot patterns (shifted MA cloud, batch-dominated PCA, anti-conservative p-value histogram), or building a standard QC figure panel.

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。