I have an in-house AI agent that triggers k6 load test based on github push or github webhook events , but it still misses two critical situations: Identifying code updates and new feature additions and update the scripts or create new scripts , I need that gap closed. Your task is to upgrade the agent so it watches a codebase , create k6 , loadrunner and selenium scripts for new features or update exiting scripts .let me implementation be Python only Once a change is spotted the agent must automatically adjust our existing automation and performance test scripts, regenerating or patching them so CI runs green without manual edits. The current pipeline is circleci -based with k6 and loadrunner for performance checks; hooks are already in place, they just need smarter input from the agent. Deliverables 1. Refactored agent source with clear comments. 2. Detection logic covering the two scenarios above, demonstrated with sample PRs. 3. Script-modification routines that update our test and load-test suites. 4. A concise README explaining setup plus a one-command demo. Acceptance will be based on a pull request against a staging branch, where your agent must detect a simulated library upgrade and a small feature file, then update the tests and performance scripts so all pipelines pass.