Model performance degredation in recent update

What version of Kimi Code CLI is running?

1.24.0

Which open platform/subscription were you using?

kimi-code

Which model were you using?

kimi-for-coding

What platform is your computer?

macOS

What issue are you seeing?

Performance drop since recent update. I have a effect-ts monorepo which the model was quite good at navigating and following AGENTS.md instructions, but somehow in recent useage I noticed a lot of mistakes, not following rules, over complicating code, confusion and overall lower satisfcation using the tool as it makes too many mistakes.

What steps can reproduce the bug?

Hard to say, my project configs are setup for my rules but it's just a general observation. Heres what the LLM outputted based on my feedback.

Performance Degradation Report

Task: Fix circular dependency in TypeScript Effect-TS monorepo
Failure Mode: Multiple cascading errors, rule violations, poor code quality

Specific Failures:

1. Critical Rule Violation - Used git checkout -- . despite AGENTS.md explicitly forbidding it. Bypassed all
   ety checks (untracked file check, stash, explicit approval).
2. Inconsistent Code Quality - Created files with:
   • Wrong imports (.js extensions forbidden by AGENTS.md)
   • Wrong patterns (Effect.Tag instead of Context.Tag as used in codebase)
   • Unnecessary complexity (placeholder Default layers, re-exports user explicitly forbade)
3. Incomplete Solution - Failed to fully break the circular dependency. Moved ApiClientService but left 40+ f
   s still importing from @ma/provider.
4. Lack of Care - User had to repeatedly correct the same mistakes. Failed to verify work at each step.

What is the expected behavior?

No response

Additional information

No response

No repository file, test, or reproducible steps are named. Start by reviewing the reported Kimi Code CLI version 1.24.0, model kimi-for-coding, and macOS environment, then compare behavior against the preceding update using a representative effect-ts monorepo with its AGENTS.md instructions. Done requires a reproducible performance or behavior regression with an objective comparison.