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
Smriti: A Git-like system for managing LLM reasoning state to prevent conversation drift
Smriti is an open-source tool that lets developers save, restore, branch, and compare reasoning states in LLM conversations to prevent drift. It treats interactions as state rather than chat history, allowing clean rollbacks and alternative exploration without contamination.
OpenClaw user creates 'feelslikeclaude' skill to improve ChatGPT agent workflow behavior
A developer switched their OpenClaw setup from Claude to ChatGPT and found the key difference was workflow behavior, not writing style. They created a clawhub skill called 'feelslikeclaude' to nudge ChatGPT toward better execution habits.
Engram: Hybrid Memory Plugin for OpenClaw Agents — Vector + Semantic Search with Decay
Engram gives OpenClaw agents persistent memory across sessions using SQLite+FTS5 for exact recall and LanceDB for semantic search, with decay classes and auto-capture hooks.
LamBench: A Lambda Calculus Benchmark Suite for AI Coding Agents
LamBench is a benchmark suite evaluating AI agents on lambda calculus tasks, measuring intelligence, speed, and elegance. The v1 release includes problems and a matrix of scores.