Show HN: Kelora – Turn messy logs into structured data (www.kelora.dev)

Kelora, a new command-line tool, has been introduced as a scriptable log processor designed to transform messy logs into structured data. It allows users to parse various log formats, apply complex filtering logic, and perform detailed analyses using embedded Rhai scripting, all within a single executable. While it's slower than tools like grep and jq, Kelora offers stateful logic and embedded scripting capabilities, making it ideal for users dealing with messy logs or requiring multi-stage transformations. It can output JSON, CSV, or Logfmt formats, facilitating integration with existing analytics tools. This tool is significant for the AI/ML community as it exemplifies the growing trend of leveraging AI in software development, with its implementation generated entirely by AI agents. Kelora's pre-1.0 status highlights its experimental nature, suggesting that it may evolve rapidly before reaching final release. The development relies on rigorous validation through an automated test suite and Rust security tools, although users are advised to approach it with caution in production environments due to potential API changes. Its advanced features, such as deep flattening of nested JSON and privacy-preserving pseudonymization, position it as a valuable asset for engineers and data scientists working with increasingly complex log data.