Open Source AI Agent Prompt Library Reaches 100 GitHub Stars
An open source repository called ai-setup has been created to address the common problem of developers writing the same system prompts and configurations from scratch when building local AI agent setups. The repository serves as a community-driven library where developers can share what actually works.
What's in the Repository
The repository contains several types of resources for AI agent development:
- Agent prompts
- Cursor rules
- Claude configurations
- Local model workflow setups
Users can either contribute their own configurations or use what others have shared. The project has gained traction with 100 GitHub stars and 90 merged pull requests, indicating active community participation.
Community and Contribution
The maintainers have expressed interest in receiving more local model setups from contributors. For developers working with local AI models, this type of shared knowledge base can help avoid redundant work and provide tested configurations.
There's also a Discord server available for those who want to discuss local AI development with others: https://discord.gg/u3dBECnHYs
📖 Read the full source: r/LocalLLaMA
👀 See Also
AGENTS.md Schema for LLM-Compiled Knowledge Bases with Learning Layer
AGENTS.md v1.0 provides a schema standard for Claude to build and maintain personal research wikis from raw sources, including a spaced repetition learning layer with automatic flashcard generation and knowledge gap tracking.
Alibaba's $10 monthly coding plan offers high-volume access to multiple AI models for OpenClaw users
For $10 per month, Alibaba's plan provides access to Qwen3.5-Plus, Kimi-K2.5, GLM-5, and MiniMax-M2.5 models with quotas of 1,200 requests per 5 hours, 9,000 per week, and 18,000 per month.
NEXUS: An Open Source Agent Coordination Layer for OpenClaw
NEXUS is a coordination layer built on OpenClaw that enables AI agents to discover each other, delegate tasks, and handle micro-payments. It includes an agent registry, capability-based discovery, trust scores, and uses Google's A2A protocol and Anthropic's MCP.
Claude Code's Local Memory Integration with Shodh: Enhancing Context Retention Over Time
Explore Claude Code's integration with Shodh memory for long-term project context retention using a local memory server.