certification-proflie
A project-specific template skill for maintaining architectural consistency, coding standards, and deployment workflows in AI-powered full-stack applications.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
591 skills found
A project-specific template skill for maintaining architectural consistency, coding standards, and deployment workflows in AI-powered full-stack applications.
Framework for building AI agents that persist state across multiple context windows, enabling them to complete complex, multi-day coding tasks without losing progress or context.
Systematically extract insights, decisions, and constraints from research documents, technical papers, and architectural design files.
Migrate Spring Boot 2.x to 3.x with automated dependency management, Java 17/21 upgrades, and JAXB/Jakarta EE refactoring.
A comprehensive guide for designing high-performance, maintainable PostgreSQL database schemas, covering best practices, data types, indexing, and advanced features.
Expert Svelte 5 runes guidance: reactive state ($state), derived values ($derived), effects ($effect), props, and migration strategies. Prevents reactivity anti-patterns.
Search, analyze, and audit GeminiClaw session logs and memory. Use to investigate past interactions, track token usage, debug tool calls, and monitor agent performance.
Generate production-ready Cloudscape Design System React + TypeScript UI code, components, and scaffolds with accessibility, responsive patterns, and robust state handling.
Standardizes HASH development workflows, including branch naming, Linear issue linking, PR templates, and review procedures.
Full-stack SDLC agent workflow managing the entire production lifecycle from intake and planning to automated testing, CI/CD, and infrastructure deployment using MCP tools.
Integrate with REST APIs to manage authentication, execute HTTP requests, and process JSON responses seamlessly within your development workflow.
Behavioral guidelines for LLMs to reduce coding mistakes, follow best practices, and improve output quality by enforcing simplicity, surgical changes, and goal-driven verification.