576 件 ・ 関連度順
概要と使いどころ
Handle confidential GitHub Security Advisory response for Paperclip. Use when coordinating advisory triage, private-fork fixes, CVE/publication steps, and immediate security releases.
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。
Modern minimal resume, single A4 page, ready for print or PDF 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。
Retrieve active cyber-threat intelligence — malware IOCs, C2 infrastructure, and CISA known-exploited vulnerabilities — filterable by type, source, and severity. Use when the user asks about current cyber threats, IOCs, or actively exploited CVEs.
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。
Assess portfolio risk using npx neural-trader — VaR, CVaR, Sharpe, position sizing, circuit breaker status
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。
Detect and classify candlestick patterns from ingested OHLCV data
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。
Ingest and normalize market data into OHLCV vectors stored by symbol and date for later pattern detection. Use when you need to load price and volume history for a symbol before running pattern detection or comparison. Read-only analysis; it never places orders.
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。
Performs Scanpy single-cell RNA-seq QC, normalization, HVG selection, PCA/UMAP/t-SNE, clustering, exploratory marker ranking, pseudobulk preparation, visualization, and Seurat or SingleCellExperiment RDS conversion to h5ad. Applies to established exploratory scRNA-seq workflows with explicit count and expression provenance; complementary skills cover scvi-tools models and AnnData format details.
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。
Queries the CZ CELLxGENE Census programmatically for versioned public single-cell and spatial transcriptomics data. Use when you need population-scale cell metadata, gene expression slices, Census summary counts, source H5AD URIs/downloads, embeddings, spatial Census data, or reference atlas comparisons across organisms, tissues, diseases, assays, and cell types. For analyzing your own local single-cell data use scanpy, anndata, or scvi-tools.
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。
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
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。
Per-token details for a specific token identified by keyword, symbol, or contract address: (1) search — find tokens by keyword/symbol/contract; (2) meta — static info: name, symbol, logo, social links, creator, official website; (3) dynamic — real-time market data: price, 24h change, volume, holder count, liquidity; (4) kline — OHLCV candlestick data for technical analysis. Use for: "price of $X", "search for token Y", "kline chart for $Z", "who created $W", "social links for $V", "holder count of $U", "candlestick data", "find the contract address of <token>".
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。
Tailors one resume to one specific job posting. Builds a must-have/nice-to-have requirement table, an evidence map, gap questions instead of invention, a tailored copy (headline, summary, bullet order, skills), honest ATS guidance, and an optional cover letter for that posting. Use when the user says "tailor my resume to this job", "customize my CV for this posting", "match my resume to this job description", "what keywords am I missing", "make my resume ATS-friendly for this role", "will this get past the ATS", "the job asks for X and I don't have it", or pastes a job ad with a resume. Works from pasted text; uses Reactive Resume MCP tools when connected. Not for bullets with no target job (resume-bullet-writer), what belongs on a resume or a general audit (resume-content-guide), tracking or follow-ups (job-application-manager), or interview prep and practice (interview-prep, mock-interview).
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。
固件 / IoT 渗透链。从拿到一坨 .bin / .img 开始，闭环走完逆向 → 提取 → 模拟 → 利用。 方法论遵循 OWASP FSTM 九阶段；工具链以 binwalk v3、unblob、EMBA、Firmadyne、AFL++ 为主。 适用场景：路由器/摄像头/智能家居固件审计、固件升级包逆向、IoT CVE 复现、嵌入式 0day 挖掘。 触发关键词：固件、firmware、IoT、binwalk、unblob、UART、JTAG、squashfs、UBI、JFFS2、Firmadyne、QEMU 全系统仿真、EMBA、固件渗透、路由器固件、嵌入式漏洞利用、bootloader、NVRAM、FAT、firmware analysis toolkit。
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。
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.
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。
Paid capability marketplace for global multi-asset data; use it when free Vibe-Trading sources lack coverage, depth, or provider quality, and keep free sources as the default for routine OHLCV.
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。
Risk measurement and stress testing — VaR/CVaR/max drawdown calculation, Monte Carlo simulation, extreme-value tail-risk analysis, and historical scenario stress testing.
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。
Core technical indicator collection (trend EMA/ADX + mean-reversion BB/RSI + volume-price OBV/volume ratio), generates a composite signal via three-dimensional voting. Pure pandas implementation for any OHLCV data.
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。
yfinance global market data interface — retrieve OHLCV and research data for US, HK, and Canadian stocks, ETFs, and indices via Yahoo Finance. Free, no API key required.
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。
Volatility strategy. Trades mean reversion based on percentile ranking of historical volatility (HV). Suitable for any OHLCV data.
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。
Seasonal/calendar-effect strategy. Generates trading signals from time-based patterns such as month-of-year effects and day-of-week effects. Suitable for any OHLCV data.
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。
Machine-learning predictive strategy based on sklearn walk-forward training, feature engineering, and signal generation. Suitable for any OHLCV data.
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。
Detect cyber attacks on OT historian servers (OSIsoft PI, Ignition, GE Proficy, Wonderware InSQL) using a Python detector that flags unauthorized queries, data manipulation, and lateral-movement indicators as historians pivot between IT and OT networks. Use when monitoring historians bridging IT/OT zones for compromise, investigating historian-specific CVE exploitation, or validating historian data integrity after a suspected OT incident.
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。
Establish a repeatable operational process for triaging, testing, and deploying Microsoft Patch Tuesday security updates (Windows, Office, Exchange, SQL Server, Azure) via WSUS/SCCM within risk-based remediation SLAs, from advisory review through validation. Use when building or improving a monthly patch management workflow or prioritizing which CVEs to remediate first.
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。
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.
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。
Audit and manage dependencies across multi-language projects. Identifies vulnerabilities, license conflicts, transitive dependency risks, and safe-upgrade paths. Use when auditing third-party packages before release, investigating a CVE, planning a major version bump, or running a license-compliance review. Examples: 'audit our npm dependencies', 'do we have GPL contamination', 'plan the upgrade to React 19'.
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。