alphaear-deepear-lite
Fetch real-time financial signals, transmission-chain reasoning, and market confidence metrics directly from the DeepEar Lite platform.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
379 skills found
Fetch real-time financial signals, transmission-chain reasoning, and market confidence metrics directly from the DeepEar Lite platform.
Generate professional pull request descriptions using Grey Haven Studio standards, ensuring clear summaries, motivation, technical implementation details, and testing strategies.
Debugging guide for AReaL distributed training issues, including hangs, NCCL errors, OOM, and numerical consistency in FSDP2/TP/CP/EP.
A comprehensive toolkit for measuring, auditing, and debugging web performance metrics including Core Web Vitals, loading speed, and interaction latency directly in Chrome DevTools.
Proactive context window management for AI agents via intelligent token monitoring, snapshot creation, and selective state rehydration to maintain continuity during long sessions.
Systematic methodology for reproducing published academic papers using provided data, including sample selection, statistical verification, and automated reporting.
Official MCP server for iOS/macOS development: streamline builds, tests, runs, debugging, and UI automation using Xcode and CLI workflows.
Generates cloud architecture diagrams directly from Terraform (.tf) files. Parses HCL, maps resource dependencies, and visualizes infrastructure automatically using Eraser.
Professional UI design system toolkit for design token generation, component architecture, responsive calculations, and developer handoff documentation to ensure visual consistency.
Automates the release workflow for Worktrunk, including version bumping, CHANGELOG generation, contributor crediting, and publishing to crates.io and GitHub.
Create polished animated terminal demos for pull requests and documentation using asciinema, agg, and svg-term-cli.
Comprehensive toolkit for graph creation, network analysis, and visualization in Python. Ideal for analyzing relationships, centrality, community detection, and synthetic network generation across diverse research domains.