523 skills · sorted by relevance
Detect PowerShell Empire framework artifacts in Windows event logs by identifying Base64 encoded launcher patterns, default user agents, staging URL structures, stager IOCs, and known Empire module signatures in Script Block Logging events.
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Windows アプリ開発 (WinUI 3 / Windows App SDK) のテスト・性能・アクセシビリティ・スレッド。 MSTest, xUnit, NUnit, WinAppDriver, Appium, Playwright, WebView2 テスト, CI, WACK, MSIX サイドローディング, version adaptive。LoggingChannel / ETW, WPT, WPA, プロファイリング, GC, 起動性能, XAML 最適化, ListView/GridView 仮想化。UI Automation, AutomationProperties, automation peers, キーボード操作性, ハイコントラスト, Narrator。DispatcherQueue, DispatcherQueueTimer, WinRT 非同期パターン, async/await, ConfigureAwait, スレッドプール, STA/MTA, デッドロック回避, バックグラウンドタスク。
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Pino (高速 JSON 構造化ロガー for Node.js、Fastify 標準ロガー) リファレンス。 logger, child logger, log levels (info / warn / error / debug / trace)、transport、 pretty print (pino-pretty)、redaction (機密情報マスキング)、serializers、 async / sync logging、ファイル出力、structured logging。
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Use when adding monitoring, metrics, logging, or tracing to Spring AI or LLM integration code. Covers token tracking, latency measurement, cost estimation, and prompt/response logging. Use when user mentions AI monitoring, token costs, or LLM observability.
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Read and analyze log entries from Cloud Logging using the gcloud CLI.
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Implement comprehensive monitoring, logging, metrics, tracing, and alerting for production applications to ensure reliability and quick incident response. Use when setting up application monitoring, implementing structured logging, creating metrics and dashboards, setting up alerts, implementing distributed tracing, monitoring performance, tracking errors, or building observability into applications.
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Design robust error handling strategies including try-catch blocks, custom error classes, error boundaries, graceful degradation, and comprehensive logging. Use when implementing exception handling, creating custom error types, setting up error boundaries in React, designing error response formats for APIs, implementing retry logic, handling async errors and promise rejections, logging errors for monitoring, creating user-friendly error messages, or building fault-tolerant systems that fail gracefully.
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Design error handling strategies for TypeScript and Python applications — exception hierarchies, Result/Either types, retry patterns, error boundaries, and structured error logging. Use when designing error handling architecture, choosing between exceptions and Result types, implementing retry logic, or building error recovery flows. Activate on "error handling", "exception hierarchy", "Result type", "retry pattern", "circuit breaker", "error boundary", "Pokemon exception". NOT for debugging specific runtime errors, logging infrastructure setup, or monitoring/alerting configuration.
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Detect PowerShell Empire framework artifacts in Windows event logs by identifying Base64 encoded launcher patterns, default user agents, staging URL structures, stager IOCs, and known Empire module signatures in Script Block Logging events.
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Parse Windows PowerShell Script Block Logs (Event ID 4104) from EVTX files to detect obfuscated commands, encoded payloads, and living-off-the-land techniques. Uses python-evtx to extract and reconstruct multi-block scripts, applies entropy analysis and pattern matching for Base64-encoded commands, Invoke-Expression abuse, download cradles, and AMSI bypass attempts.
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Creates consistent error handling with custom error classes, HTTP status mapping, structured logging, safe client messages, and error taxonomy. Use when standardizing "error handling", "logging", "error responses", or "exception management".
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Complete observability & reliability engineering system. Use when designing monitoring, implementing structured logging, setting up distributed tracing, building alerting systems, creating SLO/SLI frameworks, running incident response, conducting post-mortems, or auditing system reliability. Covers all three pillars (logs/metrics/traces), alert design, dashboard architecture, on-call operations, chaos engineering, and cost optimization.
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Build or review Java services with Quarkus 3.x using patterns for REST APIs, database access with Panache, and messaging with Apache Camel. Examples cover layered code structure, validation, transactions, and asynchronous processing, where work completes separately from the main flow.
Plan literature searches, screen academic and technical sources, and combine findings into a cited review. Records search methods and exclusions, compares conflicting evidence, identifies research gaps, and checks references so readers can trace the review's claims.
Implement and review security measures in Quarkus applications. Covers sign-in, access permissions, input validation, password hashing, secret storage, request limits, audit logs, and checks for known vulnerabilities in dependencies, with implementation and configuration examples.
Review Django authentication, permissions, input handling, and production settings. Use concrete configuration and code examples to address malicious queries, unwanted requests, injected scripts, unsafe uploads, and API access, alongside secret management and security logging.
Helps organize PyTorch model training with LightningModule and Trainer, including validation, logging, model saving, and early stopping. It also guides distributed training across multiple GPUs and settings for reduced-precision computation.
Add logs, metrics, traces that follow requests across services, and actionable alerts to production features. This skill guides signal design, request identification, response instructions, and checks that the collected data can explain failures.
Set up and check OmniRoute authentication for API access and dashboard sessions. Use Bearer credentials for remote requests, manage login cookies, inspect authentication status, and configure OIDC, a standard for signing in through an identity provider.
Build Python APIs with FastAPI using clear routes, validated inputs, and consistent error handling. It guides asynchronous database and API calls, reusable dependencies, caching, and code organization to support readable implementations and responsive services.
Choose an agent and model tier using the task description and learned patterns. The skill can explain its recommendation, use compiler-based edits for supported simple changes, and record task outcomes to inform future routing decisions.
Check text, code, and configuration files for personal information and secrets before committing, logging, storing, or sending them. Identify categorized findings, flag their locations, and suggest redaction to hide sensitive details.
Run one cycle of autonomous task work in Claude Code: check progress, select and execute the next action, log the work, and schedule another cycle. Stop when all tasks are complete or the iteration limit is reached.
Review how a website behaves when images fail to load and add fallback images or meaningful placeholder content. Check loading behavior, consider loading placeholders, and use error logging and browser developer tools to investigate and verify fixes.