Data & Analytics

Operational probability, calibration, and expected-value discipline for YURI OS decisions under uncertainty. Use when making or supporting a decision involving task priority, route selection, risk acceptance, opportunity ranking, forecast-backed planning, resource allocation, go/no-go judgment, escalation threshold, or postmortem calibration — e.g. '/yuri probability', '/probability', or '/pdc'.

Use when the user wants to know what will break if they change something, or needs safety analysis before editing code. Examples: \"Is it safe to change X?\", \"What depends on this?\", \"What will break?\"

Triages security alerts in Splunk Enterprise Security by classifying severity, investigating notable events, correlating related telemetry, and making escalation or closure decisions using SPL queries and the Incident Review dashboard. Use when SOC analysts face queued alerts from correlation searches, need to prioritize investigation order, or must document triage decisions for handoff to Tier 2/

Reverse engineers malware binaries using NSA''s Ghidra disassembler and decompiler to understand internal logic, cryptographic routines, C2 protocols, and evasion techniques at the assembly and pseudo-C level. Activates for requests involving malware reverse engineering, disassembly analysis, decompilation, binary analysis, or understanding malware internals.

Implement Amazon Macie to automatically discover, classify, and protect sensitive data in S3 buckets using machine learning and pattern matching for PII, financial data, and credentials detection.

Identify command-and-control beaconing patterns in network traffic by applying statistical frequency analysis, jitter calculation, and coefficient of variation scoring to detect periodic callbacks from compromised endpoints.

Detects credential stuffing attacks by analyzing authentication logs for login velocity anomalies, ASN diversity, password spray patterns, and geographic distribution of failed logins. Uses statistical analysis on Splunk or raw log data. Use when investigating account takeover campaigns or building detection rules for auth abuse.

Performs statistical analysis of Zeek conn.log connection intervals to detect C2 beaconing patterns. Uses the ZAT library to load Zeek logs into Pandas DataFrames, calculates inter-arrival time standard deviation, and flags periodic connections with low jitter. Use when hunting for command-and-control callbacks in network data.

Detect unusual API call patterns in AWS CloudTrail logs using boto3, statistical baselining, and behavioral analysis to identify credential compromise, privilege escalation, and unauthorized resource access.

Detects anomalous authentication patterns using UEBA analytics, statistical baselines, and machine learning models to identify impossible travel, credential stuffing, brute force, password spraying, and compromised account behaviors across authentication logs. Activates for requests involving authentication anomaly detection, login behavior analysis, UEBA implementation, or suspicious sign-in inve

This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices,

Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.

Detect abnormal access patterns in AWS S3, GCS, and Azure Blob Storage by analyzing CloudTrail Data Events, GCS audit logs, and Azure Storage Analytics. Identifies after-hours bulk downloads, access from new IP addresses, unusual API calls (GetObject spikes), and potential data exfiltration using statistical baselines and time-series anomaly detection.

Parses API Gateway access logs (AWS API Gateway, Kong, Nginx) to detect BOLA/IDOR attacks, rate limit bypass, credential scanning, and injection attempts. Uses pandas for statistical analysis of request patterns and anomaly detection. Use when investigating API abuse or building API-specific threat detection rules.

Turn any codebase into a beautiful, interactive single-page HTML course that teaches how the code works to non-technical people. Use this skill whenever someone wants to create an interactive course, tutorial, or educational walkthrough from a codebase or project. Also trigger when users mention 'turn this into a course,' 'explain this codebase interactively,' 'teach this code,' 'interactive tutorial from code,' 'codebase walkthrough,' 'learn from this codebase,' or 'make a course from this p...

Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources, or leverage BigQuery's built-in ML capabilities. Also use when performing data analysis, ingesting data into BigQuery, or developing AI applications on BigQuery.

@Observableを使用した状態管理、ビュー合成、ナビゲーション、パフォーマンス最適化、モダンなiOS/macOS UIのベストプラクティスを備えたSwiftUIアーキテクチャパターン。

Data analysis assistant. Analyzes CSV/JSON data, generates statistical reports and visualizations. Triggers: data analysis, csv analysis, json parser, data insights.

Machine learning skill: find, explain, and implement ML algorithms with interactive Jupyter Notebook links. Covers linear regression, logistic regression, neural network, K-Means clustering, anomaly detection — with math, Python code, and skill demos.

Excel/CSV data quality diagnosis & interactive charts — 20+ scan modules, 6-dimension scoring, agent-powered semantic analysis, and any ECharts visualization. Fully local. Activate this skill whenever the user uploads, attaches, or mentions a .csv, .xlsx, .xls, or .tsv file, even without an explicit request. Present the skill menu immediately.

> 版本：1.0.0 > 描述：免费网页抓取 + 内容提取 + 结构化输出，无需付费API ---

- **2013**: 由Apache Spark创始人Matei Zaharia及UC Berkeley AMPLab团队成员在旧金山创立，初始愿景是让Spark在企业中更易用 - **2014**: 发布首个托管Spark服务，定位为"Spark as a Service"，解决企业自行部署Spark集群的运维痛点 - **2016**: 推出Databricks Delta（后更名为Delta Lake），引入ACID事务到数据湖，解决数据湖的可靠性问题 - **2019**: 发布Delta Lake开源版本，同时推出MLflow实验管理工具，构建完整MLOps生态 - **2021**: 提出"Lakehouse"架构概念，融合数据仓库的结构化查询能力与数据湖的灵活性 - **2022**: 收购8080 Labs（munity.ai），推出DBRX大语言模型训练基础设施 - **2023**: 发布Unity Catalog实现跨工作区统一治理，估值达430亿美元，提交IPO申请 - **2024**: Databricks IQ（AI助手）和Lakeflow产品发布，年经

- **名称**: data-viz-reporter - **描述**: 专业的商业数据可视化报告生成工具，将枯燥的数据转化为直观、美观、有洞察力的图表和报告 - **版本**: 1.0.0 - **适用场景**: 电商数据分析、运营周报/月报、市场调研、财务报表、用户分析等商业场景

智能文件/桌面整理技能。当用户说"整理桌面"、"文件整理"、"整理文件夹"、"清理桌面"时触发。提供零删除、零篡改的安全文件归类，支持智能扫描、关键词匹配、按类型自动分类、多平台支持（macOS/Linux/Windows）。