design-review
Designer's eye QA: detects and automates fixes for visual inconsistencies, spacing, hierarchy, and UI polish issues. Iteratively verifies with before/after screenshots.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
448 skills found
Designer's eye QA: detects and automates fixes for visual inconsistencies, spacing, hierarchy, and UI polish issues. Iteratively verifies with before/after screenshots.
Orchestrate parallel Claude Code worker swarms with protocol-based behavioral governance for complex features, multi-step refactors, and long-running autonomous coding sessions.
Build no-code MCP servers that orchestrate tools as directed graphs using YAML for data transformation, conditional routing, and automated workflows.
A comprehensive library of 305+ modular instruction packages, Python CLI tools, and agent workflows designed to extend the capabilities of AI coding assistants like Claude Code, Cursor, Aider, and Gemini CLI.
Implement Google Gemini API audio capabilities: process, transcribe, and summarize audio files, analyze environmental sounds, and generate natural speech with controllable TTS.
Build interactive, hypermedia-driven web applications using Rust, Axum, and HTMX for dynamic, real-time UI updates without complex JavaScript frameworks.
Implementation and maintenance guide for the atopile Language Server (LSP), providing IDE features like autocomplete and diagnostics for electronics design.
Retrieve current, source-backed technical information using MCP tools to resolve queries about libraries, APIs, SDKs, and evolving tech ecosystems.
Interactive CLI-based issue management system for tracking, planning, and executing development tasks with full CRUD capabilities.
Implement ReasoningBank adaptive learning with AgentDB's ultra-fast vector backend. Features trajectory tracking, verdict judgment, memory distillation, and pattern recognition for self-learning autonomous agents.
Epistemic safety analysis for JSON data in prompts to prevent LLM hallucinations and reasoning errors when handling incomplete or large-scale datasets.
Supermemory is a long-term memory infrastructure for AI agents, enabling persistent context, user profiles, and semantic RAG across multi-modal knowledge bases.