productivity▌

此技能用于抓取今日头条 PC 端热榜（hot-board）数据，包括：

Skill by ara.so — Daily 2026 Skills collection.

Temporal is a durable execution platform that makes workflows survive failures automatically. This skill provides guidance for building Temporal applications in Python, TypeScript, Go, and Java.

Reflect on previus response and output.

Decision guide for Stripe API selection, Connect setup, billing, and integration patterns. \n \n Routes integration decisions across six domains: one-time payments (Checkout Sessions), custom payment forms (Payment Element), saved payment methods (Setup Intents), marketplaces (Accounts v2), subscriptions (Billing APIs), and embedded financial accounts (Treasury) \n Provides reference documentation for each integration type, including API version guidance (latest: 2026-02-25.clover) and pre-launc

Mamba is a state-space model architecture achieving O(n) linear complexity for sequence modeling.

Design and implement comprehensive backup and disaster recovery strategies to ensure data protection, business continuity, and rapid recovery from infrastructure failures.

Master Inngest event design and delivery patterns. Events are the foundation of Inngest - learn to design robust event schemas, implement idempotency, leverage fan-out patterns, and handle system events effectively.

Structured problem-solving through iterative reasoning with revision and branching capabilities. \n \n Break complex problems into sequential thought steps with dynamic scope adjustment as understanding evolves \n Revise previous conclusions and explore alternative reasoning paths from any point in the analysis \n Maintains full reasoning chain context throughout multi-stage analysis, design planning, or problem decomposition \n Ideal for tasks with initially unclear scope, interconnected reason

Production-grade computer vision expertise for image/video processing, object detection, model training, and inference optimization. \n \n Covers advanced architectures, real-time inference systems, and scalable data pipelines with distributed computing frameworks (Spark, Airflow, Kafka) \n Includes object detection optimization, model deployment strategies, and production monitoring with MLflow and Weights & Biases \n Supports PyTorch, TensorFlow, YOLO, and vision transformers with contain