SCENARIO
数据分析 Skills
Data Analysis
数据处理、统计分析与可视化
数据分析 的 Skills 2153
health
Code quality dashboard. (gstack)
dataviz
Choose and produce an appropriate chart/dashboard/visual explanation from data, with legible encodings and source/assumption notes.
pr-dashboard
Open a GitHub PR dashboard in the browser. Use when the user asks to see their pull requests, open the PR dashboard, show PRs for a date range, or check PR status. Trigger phrases include "show my PRs", "open PR dashboard", "pull request dashboard".
power-bi-report-design-consultation
Power BI report visualization design prompt for creating effective, user-friendly, and accessible reports with optimal chart selection and layout design.
lightweight-charts-react-components
lightweight-charts-react-components recipes for TradingView lightweight-charts in React. Candlestick, line, and area series; volume and indicator panes; realtime WebSocket updates; infinite history on scroll; crosshair OHLC legends and tooltips; trade markers and price lines; synchronized charts; numeric options and yield-curve axes. Use when adding or fixing a financial or trading chart in a React app, or when the user mentions lightweight-charts, TradingView charts in React, or this package.
folder-structure-blueprint-generator
Comprehensive technology-agnostic prompt for analyzing and documenting project folder structures. Auto-detects project types (.NET, Java, React, Angular, Python, Node.js, Flutter), generates detailed blueprints with visualization options, naming conventions, file placement patterns, and extension templates for maintaining consistent code organization across diverse technology stacks.
securing-helm-chart-deployments
Secures Helm chart deployments by verifying chart signatures and provenance, rendering and linting templates for misconfiguration, enforcing pod security contexts through values.yaml, moving secrets into an external store instead of Helm values, and scoping RBAC for Helm operations in CI/CD. Use when deploying charts to Kubernetes or reviewing chart provenance, templates, or release RBAC. Keywords: Helm, provenance file, helm verify, helm lint, values.yaml, Tiller-less, release RBAC, external secrets. Do not use for scanning the rendered manifests themselves - use scanning-kubernetes-manifests-with-kubesec.
performing-user-behavior-analytics
Performs User and Entity Behavior Analytics (UEBA) to detect anomalous user activities including impossible travel, unusual access patterns, privilege abuse, and insider threats using SIEM-based behavioral baselines and statistical analysis. Use when SOC teams need to identify compromised accounts or insider threats through deviation from established behavioral norms.
performing-insider-threat-investigation
Investigates insider threat incidents involving employees, contractors, or trusted partners who misuse authorized access to steal data, sabotage systems, or violate security policies, combining digital forensics, user behavior analytics, and HR/legal coordination to build an evidence-based case. Use when DLP alerts flag large data transfers to personal cloud storage or USB devices, when UBA detects anomalous access patterns for a user account, or when investigating employee data theft, privilege misuse, or internal threat detection requests.
implementing-network-traffic-baselining
Builds network traffic baselines from NetFlow/IPFIX CSV or JSON exports using Python pandas, computing hourly/daily volume distributions, per-host and protocol/port statistics, and top-talker profiles, then flags outliers via z-score and IQR anomaly detection. Use when a SOC analyst needs to establish normal traffic patterns and surface deviations such as data exfiltration spikes, beaconing, or unusual port usage from historical flow data.
implementing-dragos-platform-for-ot-monitoring
Deploys and configures Dragos Platform sensors and detection analytics for OT/ICS network monitoring, using industrial protocol parsers and threat-intel packs to detect groups like VOLTZITE, CHERNOVITE, and KAMACITE. Use when standing up OT-specific network detection and response or an OT SOC, or integrating OT monitoring into an enterprise SIEM; not for IT-only or Claroty/Nozomi environments.
implementing-cisa-zero-trust-maturity-model
Assess, gap-analyze, and progressively implement the CISA Zero Trust Maturity Model v2.0 across five pillars (Identity, Devices, Networks, Applications & Workloads, Data) and three cross-cutting capabilities (Visibility/Analytics, Automation/Orchestration, Governance), from Traditional through Optimal maturity. Use for a federal/enterprise ZTMM assessment, phased roadmap, or mapping controls to NIST SP 800-207 and EO 14028.
implementing-azure-defender-for-cloud
Enable Microsoft Defender for Cloud (CSPM + CWPP) across VMs, containers, SQL, storage, and Key Vault, using Azure Policy for evaluation, Log Analytics for telemetry, Azure Arc for hybrid coverage, and Logic Apps for automated response. Use for Azure security monitoring, adaptive remediation, or regulatory compliance assessment; not for non-Azure-only protection or identity defense (Defender for Identity).
detecting-shadow-it-cloud-usage
Detect unauthorized SaaS and cloud service usage (shadow IT) by parsing proxy access logs, DNS query logs, and firewall/netflow data with Python pandas to aggregate traffic by domain, classify domains against known SaaS categories, and score risk by data volume and user count. Use when auditing an organization for unsanctioned cloud/SaaS usage or generating a shadow IT discovery report with remediation recommendations.
detecting-insider-threat-with-ueba
Implement User and Entity Behavior Analytics (UEBA) using Elasticsearch/OpenSearch to build behavioral baselines, calculate anomaly scores, perform peer group analysis, and alert on insider threat indicators such as data exfiltration, privilege abuse, and unauthorized access. Use when building or tuning a UEBA pipeline rather than a one-off manual hunt.
detecting-insider-data-exfiltration-via-dlp
Detects insider data exfiltration by analyzing DLP policy violations, file access patterns, upload volume anomalies, and off-hours activity in endpoint and cloud logs. Uses pandas for behavioral analytics and statistical baselines. Use when investigating insider threats or building user behavior analytics for data loss prevention.
detecting-entra-offensive-tools-in-graph-logs
Hunt AADGraphActivityLogs and MicrosoftGraphActivityLogs in Microsoft Sentinel/Log Analytics using KQL to fingerprint offensive Entra ID enumeration tools such as ROADtools, AADInternals, and AzureHound, including User-Agent signatures, roadrecon endpoint sweeps, and sign-in correlation. Use when investigating suspicious Microsoft Graph API activity, Entra ID reconnaissance, or building Sentinel analytics rules to detect these tools.
detecting-business-email-compromise
Detect Business Email Compromise (BEC) fraud, where attackers impersonate executives or vendors to trick employees into wire transfers or data disclosure without malicious links, using email gateway rules, behavioral analytics, and financial process controls. Use when investigating a suspected executive/vendor impersonation email or building detection rules for social-engineering fund-transfer fraud.