memov
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
191 skills found
AI-assisted version control for code agents. Track prompts, context, and diffs automatically with MemoV to ensure full traceability without polluting your git history.
Unified CLI tool to read, query, discover, and write AI agent conversations using the agents:// URI scheme across multiple coding agents and providers.
Validate and enforce consistent markdown document structure, including YAML frontmatter positioning, correct heading hierarchy, and logical content organization for Obsidian vaults.
Evidence-based debugging for Python, Node.js, and Java applications using runtime execution traces and diagnostic MCP tools.
Intelligent pattern selection for Fabric CLI, automatically choosing from 242+ specialized prompts for threat modeling, data analysis, summarization, and content creation.
Guidelines for curating high-quality datasets for LLM post-training (SFT/DPO/RLHF), covering data formats, quality filtering, and collection strategies.
Manage Jules (Google's async AI coding agent) directly from your terminal. Create, monitor, and interact with Jules coding sessions, approve plans, and handle feedback loops across repositories.
Unified AI gateway for building full-stack apps and automating tasks. Access 100+ AI models for content generation, web scraping, app deployment, and Stripe payments with a single API key.
Build stateful AI agents on Cloudflare Workers using the Agents SDK. Features real-time WebSockets, persistent state management, scheduled background tasks, and native tool integration for production-ready deployments.
A framework for applying Test-Driven Development to process documentation, ensuring agent reliability by using pressure scenarios to identify and patch rationalization loopholes.
Architect production-grade LLM applications using LangChain 1.x and LangGraph. Implement stateful AI agents, multi-step workflows, and custom memory systems for complex conversational and automation tasks.
Analyze project codebases to generate architecture documentation, coding standards, and development practices for AI onboarding.