skill-memory
A Git-backed memory store for agent skills. Download, version, edit, and share custom agent behaviors and procedural knowledge using a CLI.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
270 skills found
A Git-backed memory store for agent skills. Download, version, edit, and share custom agent behaviors and procedural knowledge using a CLI.
Build modern, composable, and accessible React UI components following the components.build specification. Use for design systems, component libraries, and reusable UI architectures.
Enables cross-session context persistence for Claude Code, managing history, project decisions, and workflow patterns to ensure seamless task continuation.
Official Mastra framework guide. Master AI agent and workflow development with local documentation lookup, API verification, and TypeScript-based project management.
Expert-level Phaser 3 game development agent. Handles scene architecture, Arcade/Matter physics, asset pipelines, sprite animations, and performance optimization for 2D web games.
Orchestrates multi-agent iterative refinement for high-quality OpenClaw skill development, ensuring rigorous testing and lifecycle management.
Generate professional Product Requirements Documents (PRD) and structure features for autonomous development cycles.
A powerful CLI for converting web content and search results into LLM-friendly formats like Markdown, text, or HTML using the Jina AI Reader API.
Generate triage reports and analyze feature area health for the Windows App SDK repository. Identify high-priority issues, triage backlogs, and team focus areas.
Automated PR lifecycle management: monitors conflicts, resolves CI failures, handles review feedback, and executes squash-merges for safe code integration.
Transforms feature requests, bug reports, and improvement ideas into structured, actionable markdown project plans using repository research and industry best practices.
Analyzes markdown files to identify token-wasting patterns, providing actionable suggestions to optimize documentation for LLM consumption and token efficiency.