context-engineering-collection
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
480 skills found
A structured repository of Agent Skills for context engineering, multi-agent architectures, and production-grade agent system optimization.
Base ecosystem skill for Refly. Creates, discovers, and runs domain-specific skills, routes user intent to workflows via symlinks, and automates multi-step pipelines via the Refly CLI.
Generate professional visual assets including app icons, logos, banners, and illustrations using the Nano Banana Pro (Gemini 3 Pro) AI model.
Self-modify your Milady agent by managing plugins. Edit code, rebuild, and restart the runtime to develop new capabilities or improve agent workflows locally.
Generate professional, cohesive, project-specific SVG icon sets with consistent style, stroke weight, and visual density. Ideal for unique web and app UI branding.
A RAG-based AI solver for high school Chinese GSAT exams, featuring structured knowledge retrieval, reasoning templates, and explainable AI outputs.
Master v-click, v-after, and motion directives in Slidev to create progressive content reveals, interactive diagrams, and complex slide animations.
Manage dlt data pipelines and Temporal workflows for the SignalRoom marketing platform. Sync sources like Everflow, Redtrack, and S3 to Postgres, check status, and debug ingestion.
Break down complex development requests into sequenced, actionable tasks for multi-agent delegation in Claude Code environments.
Evaluate Deca agent prompts and behavioral consistency through automated test runners, manual LLM judgment, and structured reporting.
Standardizes markdown content with active voice, precise heading hierarchies, and WCAG AA accessibility compliance for documentation, web sites, and repository files.
Analyze codebase statistics: LOC, language distribution, and code-to-comment ratios using pygount.