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Found 1,666 Skills
Comprehensive toolkit for generating best practice Fluent Bit configurations. Use this skill when creating new Fluent Bit configs, implementing log collection pipelines (INPUT, FILTER, OUTPUT sections), or building production-ready telemetry configurations.
MongoDB development guidelines with Payload CMS, Mongoose, aggregation pipelines, and TypeScript best practices.
Automate Android screenshot capture across devices and locales using adb, Espresso/UI Automator, device framing, and gplay CLI upload. Use when building screenshot pipelines for Google Play listings.
Angular 19 patterns: signals, standalone components, resource API, signal queries, dependency injection, and Aurora framework integration. Trigger: When implementing Angular components, directives, pipes, services, or using modern reactive patterns.
Professional DevOps engineering skill for creating CI/CD pipelines, implementing infrastructure as code, managing environments, and establishing monitoring and observability across all deployment stages.
Data engineering, machine learning, AI, and MLOps. From data pipelines to production ML systems and LLM applications.
Implements the Chain of Responsibility pattern in Python. Use when the user mentions chain of responsibility, CoR, or when you need to chain handlers that each process and pass to the next—validation pipelines, processing steps, transformation chains, or any sequential pipeline.
Automated release coordination and deployment with swarm orchestration for seamless version management, testing, and deployment across multiple packages. Use for release pipelines, version coordination, deployment orchestration, and release documentation.
This skill should be used when the user asks to "design interview processes", "create hiring pipelines", "calibrate interview loops", "generate interview questions", "design competency matrices", "analyze interviewer bias", "create scoring rubrics", "build question banks", or "optimize hiring systems". Use for designing role-specific interview loops, competency assessments, and hiring calibration systems.
Reporting pipelines for CSV/JSON/Markdown exports with timestamped outputs, summaries, and post-processing.
Evaluate LLM systems using automated metrics, LLM-as-judge, and benchmarks. Use when testing prompt quality, validating RAG pipelines, measuring safety (hallucinations, bias), or comparing models for production deployment.
Design-to-code pipeline: extract copy from URLs, extract design tokens from images, then build React components or HTML preview variants. Use when: extracting content from websites, extracting design systems, generating frontend code, previewing design variants, sending to Figma via MCP. Triggers on "extract copy", "extract design", "build frontend", "generate variants", "export design", "send to Figma".