Feedback Request: LogSlimmer – Semantic Log Compression for Vibe Coders #1
Description
Hello VibeCoding community!
We're excited to share LogSlimmer, a semantic log compression tool that reduces console and terminal logs by up to 90% while keeping critical context. It's built to support AI-driven development and vibe coding workflows by improving observability and saving token usage in LLM sessions.
Key points:
- \ud83d\udd0d Semantic compression of logs to minimize noise while preserving meaning.
- \u26a1 Up to 90% reduction in log size, optimizing LLM token consumption.
- \ud83e\uddf9 Easy integration: CLI built in Python with Click; works on JSON/plaintext logs.
Live demo: https://aredesrafa.github.io/logslimmer/
We're seeking sincere feedback on performance, developer experience, and features you'd like to see. Please try the live demo and let us know:
- How well does it fit into your vibe coding flows?
- What metrics or output formats would be most valuable?
- Any integration ideas with existing observability stacks?
Also feel free to star the repo if you find it useful! https://github.com/aredesrafa/logslimmer
Thanks for your time and vibes!