vvm
VVM (Vibe Virtual Machine) is a language for agentic programs where the LLM acts as the runtime. Orchestrate multi-agent workflows, manage state, and build resilient AI pipelines.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
488 skills found
VVM (Vibe Virtual Machine) is a language for agentic programs where the LLM acts as the runtime. Orchestrate multi-agent workflows, manage state, and build resilient AI pipelines.
Automated academic literature retrieval, structured summarization, and multi-channel scheduling workflow for research topics.
Transform AI agents into proactive partners using WAL Protocol, persistent memory buffers, and autonomous cron scheduling to anticipate needs and improve performance.
Manage database orchestration sessions, state snapshots, and system-level operations for the BAZINGA-DB core engine.
Intelligent GitHub release orchestration using AI swarms for automated versioning, multi-platform deployment, testing, and rollback management.
High-quality Feishu/Lark Docx writing via OpenClaw. Convert Markdown into well-formatted Feishu Docx with support for headings, lists, nesting, and code blocks using feishu_docx_write_markdown.
Accelerate clinical and healthcare app development in Lovable. Perfect for OpenClaw Clinical Hackathon participants building MVPs with PHI-safe patterns.
Dialectical reasoning and adversarial coding agent for MCP-enabled editors, forcing LLMs to resolve internal contradictions for higher quality outputs.
Unified CLI tool to read, query, discover, and write AI agent conversations using the agents:// URI scheme across multiple coding agents and providers.
A unified document processing gateway for PDF parsing, text extraction, conversion, and document manipulation across multiple local and cloud providers.
CMMI-based SDLC router providing process guidance, requirements management, architectural decision support, quality assurance, and governance for GitHub and Azure DevOps workflows.
Operate the btca CLI for source-first code research. Manage git, local, and npm resources to ground AI answers in actual codebase context rather than outdated documentation.