Loading...
Loading...
Found 1,575 Skills
Alibaba Cloud RDS Copilot intelligent operations assistant skill. Used for RDS-related intelligent Q&A, SQL optimization, instance operations, and troubleshooting. Calls RdsAi OpenAPI through Alibaba Cloud CLI to get real-time RDS Copilot responses. Triggers: "RDS Copilot", "RDS Assistant", "SQL optimization", "RDS troubleshooting", "RDS operations", "database diagnosis"
Dockerfile optimization guidelines from official Docker documentation. This skill should be used when writing, reviewing, or refactoring Dockerfiles to ensure optimal build time, image size, security, and robustness. Triggers on tasks involving Dockerfile creation, Docker image builds, container optimization, multi-stage builds, build cache, or Docker security hardening.
Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.
Ultra-lightweight channel for refactor processes - used when changes are clearly too small to go through the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step human verification required. Trigger scenarios: User says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip the extra steps", and the scope of changes is clearly localized to a single function / single component with test coverage for self-validation.
Phase 3 of the issue workflow —— Fix code precisely according to confirmed root causes and solutions, verify the results, and document it in {slug}-fix-note.md. This is the final stage of the issue workflow —— no verification closure means the workflow is incomplete. Two entry points: the standard path is triggered from cs-issue-analyze (with existing {slug}-analysis.md), and the fast track is triggered directly from cs-issue-report (without {slug}-analysis.md, as the root cause was identified by AI through code reading during the report phase). Trigger scenarios: User says "Start fixing the bug", "Fix according to the analysis", "Start modifying the code". During the fix, only modify the files specified in the solution; do not make incidental optimizations or introduce new abstractions —— these actions will cause the scope to expand to an untraceable extent.
Three.js textures - texture types, UV mapping, environment maps, texture settings. Use when working with images, UV coordinates, cubemaps, HDR environments, or texture optimization.
Comprehensive backend development skill for building scalable backend systems using NodeJS, Express, Go, Python, Postgres, GraphQL, REST APIs. Includes API scaffolding, database optimization, security implementation, and performance tuning. Use when designing APIs, optimizing database queries, implementing business logic, handling authentication/authorization, or reviewing backend code.
Comprehensive frontend development skill for building modern, performant web applications using ReactJS, NextJS, TypeScript, Tailwind CSS. Includes component scaffolding, performance optimization, bundle analysis, and UI best practices. Use when developing frontend features, optimizing performance, implementing UI/UX designs, managing state, or reviewing frontend code.
Nest.js framework expert specializing in module architecture, dependency injection, middleware, guards, interceptors, testing with Jest/Supertest, TypeORM/Mongoose integration, and Passport.js authentication. Use PROACTIVELY for any Nest.js application issues including architecture decisions, testing strategies, performance optimization, or debugging complex dependency injection problems. If a specialized expert is a better fit, I will recommend switching and stop.
Expert prompt engineer specializing in advanced prompting techniques, LLM optimization, and AI system design. Masters chain-of-thought, constitutional AI, and production prompt strategies. Use when building AI features, improving agent performance, or crafting system prompts.
Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.
World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.