Rocky Linux 8/9 core system administration including dnf/yum package management, module streams, systemd service and timer management, user/group administration, sudo configuration, and cron...
Use this skill when users need to set up customer support systems, create help docs/FAQs, implement ticketing, build self-service resources, or optimize support operations. Activates for "too many...
Technical architect assistant that helps design robust, scalable, and maintainable backend/frontend architectures. Provides visual diagrams, pattern recommendations, API design guidance, and stack...
Create effective debugging prompts—include error messages, stack traces, expected vs actual behavior, logs, and attempted solutions
Guides using bun.sys for system calls and file I/O in Zig. Use when implementing file operations instead of std.fs or std.posix.
Memory is the cornerstone of intelligent agents. Without it, every interaction starts from zero. This skill covers the architecture of agent memory: short-term (context window), long-term (vector...
Validate design systems for accessibility (WCAG), responsive design, and component consistency with design token analysis.
Build event-driven architectures on AWS serverless infrastructure. Designs event flows, integrates Lambda with event sources, and manages distributed systems.
A reasoning pattern for diagnosing and fixing bugs that span multiple abstraction layers in complex systems.
Verify operating system hardening using CIS benchmarks with patch management, kernel hardening, and host-based firewall validation.
Create System Requirements (SYS) - Layer 6 artifact defining functional requirements and quality attributes
Skip to content github / docs Code Issues 80 Pull requests 35 Discussions Actions Projects 2 Security Insights Merge branch 'main' into 1862-Add-Travis-CI-migration-table ...
LLM application architecture expert for RAG, prompting, agents, and production AI systemsUse when "rag system, prompt engineering, llm application, ai agent, structured output, chain of thought,...
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Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming
Extract design systems from reference UI images and generate implementation-ready UI design prompts. Use when users provide UI screenshots/mockups and want to create consistent designs, generate...
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Guide for AI Agents and LLM development skills including RAG, multi-agent systems, prompt engineering, memory systems, and context engineering.