by CoderCookE · Agent Tool · ★ 269
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
vim-llm-agent A full-featured LLM agent for Vim with multi-provider support and autonomous tool execution capabilities. This plugin brings the power of AI language models and agentic workflows directly into your Vim editor. Go beyond simple chat - the agent can autonomously execute file operations, git commands, and complex multi-step tasks with plan approval and tool calling. Key Features: 🤖 Agentic Workflows - Plan approval system with autonomous tool execution 🔧 Tool Calling - File operations, git integration, project exploration 💬 Context-Aware - Session persistence, conversation summaries, project context 🔄 Multi-Provider - OpenAI, Anthropic (Claude), Google (Gemini), Ollama, OpenRouter 📝 Code Intelligence - Explain, review, refactor code with visual selections Supported Providers: OpenAI (ChatGPT, GPT-4, GPT-4o, etc.) Anthropic (Claude 3.5 Sonnet, Claude 3 Opus, etc.) Google (Gemini) Ollama (local models - Llama, Mistral, etc.) OpenRouter (unified API for 100+ models) Note: This plugin was previously named . It has been renamed to to better reflect its multi-provider capabilities.
| Stars | 269 |
| Forks | 35 |
| Language | Python |
| Category | Agent Tool |
| License | Unlicense |
| Quality Score | 29.95/100 |
| Open Issues | 6 |
| Last Updated | 2026-02-25 |
| Created | 2023-03-30 |
| Platforms | python |
| Est. Tokens | ~34k |
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vim-llm-agent is Vim Plugin For ChatGPT. It is categorized as a Agent Tool with 269 GitHub stars.
vim-llm-agent is primarily written in Python.
You can find installation instructions and usage details in the vim-llm-agent GitHub repository at github.com/CoderCookE/vim-llm-agent. The project has 269 stars and 35 forks, indicating an active community.
vim-llm-agent is released under the Unlicense license, making it free to use and modify according to the license terms.
The top alternatives to vim-llm-agent on Agent Skills Hub include claude-forge, excalidraw-diagram-skill, agent-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.