fp-pipe-ref
Quick reference for pipe and flow in fp-ts. Use to chain functions, compose operations, or build clean, readable data pipelines in functional TypeScript code.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
143 skills found
Quick reference for pipe and flow in fp-ts. Use to chain functions, compose operations, or build clean, readable data pipelines in functional TypeScript code.
Control and monitor Xiaomi Mijia smart home devices including status switching, device discovery, automation scenes, and environmental statistics.
Systematic performance engineering: baseline measurement, profiling, bottleneck diagnosis, and evidence-based optimization guidance for high-performance applications.
Build performant Three.js web scenes using modern ES modules. Includes scene graph setup, lighting, geometries, GLTF/GLB loading, animation loops, and performance optimization best practices.
Automate Python scripting and Gemini-powered image generation using uv. Ideal for creating art, editing images, and running ad-hoc scripts.
Expert guide for OpenCode AI: TUI commands, CLI operations, AGENTS.md configuration, custom agent workflows, and project setup.
Systematically trace code flows, locate implementations, diagnose performance issues, and map system architecture to understand complex codebases.
Implement production-grade AI agents with LangGraph, tool-calling guardrails, SSE streaming, and episodic memory. Includes anti-patterns, fix pairs, and stateful architecture patterns.
Analyze local system hardware (RAM, CPU, GPU/VRAM) to receive expert recommendations for optimized local LLM models, quantization settings, and performance estimates.
Access AI-ready datasets, benchmarks, and molecular oracles for drug discovery, including ADME, toxicity, DTI, and molecular generation tasks.
Execute implementation plans in separate sessions with review checkpoints, ensuring task-by-task verification and robust code quality.
World-class senior data engineering skill for building scalable data pipelines, ETL/ELT systems, and modern data infrastructure using Python, Spark, dbt, and Kafka.