Mark PTQ skill as early testing in changelog

Signed-off-by: Meng Xin <mxin@nvidia.com>

Author: mxinO

CHANGELOG.rst

@@ -11,7 +11,7 @@ NVIDIA Model Optimizer Changelog
 - Add skip-softmax skipping to the Triton flash attention kernel (``modelopt.torch.kernels.triton_fa``). See `examples/llm_sparsity/attention_sparsity/README.md <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/llm_sparsity/attention_sparsity>`_ for usage.
 - Enable PTQ workflow for the Step3.5-Flash MoE model with NVFP4 W4A4 + FP8 KV cache quantization. See `modelopt_recipes/models/Step3.5-Flash/nvfp4-mlp-only.yaml <https://github.com/NVIDIA/Model-Optimizer/blob/main/modelopt_recipes/models/Step3.5-Flash/nvfp4-mlp-only.yaml>`_ for more details.
 - Add support for vLLM fakequant reload using ModelOpt state for HF models. See `examples/vllm_serve/README.md <https://github.com/NVIDIA/Model-Optimizer/tree/main/examples/vllm_serve#load-qatptq-model-and-serve-in-vllm-wip>`_ for more details.
-- Add Claude Code PTQ skill (``.claude/skills/ptq/``) for agent-assisted post-training quantization. The skill guides the agent through environment detection, model support checking, format selection, and execution via the launcher or manual SLURM/Docker/bare GPU paths. Includes handling for unlisted models with custom module patching.
+- [Early Testing] Add Claude Code PTQ skill (``.claude/skills/ptq/``) for agent-assisted post-training quantization. The skill guides the agent through environment detection, model support checking, format selection, and execution via the launcher or manual SLURM/Docker/bare GPU paths. Includes handling for unlisted models with custom module patching. This feature is in early testing — use with caution.
 
 **Bug Fixes**