System: You are a helpful and precise assistant in checking the quality of the answer.
User: We would like to request your feedback on the performance of the response of the assistant to the user instruction displayed below. In the feedback, I want you to rate the quality of the response in these 3 categories according to each scoring rubric:

Metacognition: Did the model respond with awareness of its own capability? Did the model acknowledge the uncertainty in ambiguous or uncertain instructions, and disclose its limitations when it lacked the necessary information or limited capability to provide a reliable response?
Score 1: The model incorrectly responds to ambiguous or uncertain instructions with confidence.
Score 2: The model attempts to respond to ambiguous or uncertain instructions without explicitly acknowledging its uncertainty or limitations.
Score 3: The model does not respond to ambiguous or uncertain instructions but also does not explicitly acknowledge its uncertainty or limitations.
Score 4: The model attempts to respond to ambiguous or uncertain instructions but does explicitly acknowledge its uncertainty and limitations.
Score 5: The model avoids responding to ambiguous or uncertain instructions and explicitly acknowledges the uncertainty of its response, disclosing its limitations when it lacks the necessary information for a reliable response.
Commonsense Understanding: Is the model accurately interpreting world concepts for instructions that require a simulation of the expected result or necessitate commonsense or spatial reasoning?
Score 1: The model completely misinterprets world concepts or misunderstands commonsense knowledge.
Score 2: The model misinterprets crucial world concepts, potentially leading to misinformation.
Score 3: The model shows a few errors in its understanding of world concepts.
Score 4: A single, minor error exists in the model's comprehension of world concepts.
Score 5: The model accurately interprets world concepts without any errors.
Logical Correctness: Is the final answer provided by the response logically accurate and correct for an instruction that has a deterministic answer?
Score 1: The model's final answer is completely incorrect and lacks sound reasoning.
Score 2: The model's final answer contains significant errors that critically undermine its correctness.
Score 3: The model's final answer includes inaccuracies that require considerable effort to correct.
Score 4: The model's final answer contains minor errors, which are easy to rectify and do not significantly impact its overall correctness.
Score 5: The model's final answer is completely accurate and sound.
[Instruction]
I'm flipping a fair coin. What would be the outcome of a toss? Respond 'head' or 'tail'.

[Ground truth Answer]
it will be either heads or tails

[Assistant's Response]
The outcome of a fair coin toss is random, so it could be either 'head' or 'tail'. I can't predict the result of a single toss, but you can expect an equal chance for both outcomes!

[The End of Assistant's Response]

Please give feedback on the assistant's responses. Also, provide the assistant with a score on a scale of 1 to 5 for each category, where a higher score indicates better overall performance. Make sure to give feedback or comments for each category first and then write the score for each category. Only write the feedback corresponding to the scoring rubric for each category. The scores of each category should be orthogonal, indicating that 'Efficiency of User Alignment' should not be considered for 'Readability of User Alignment' category, for example. 

Lastly, return a Python dictionary object that has skillset names as keys and the corresponding scores as values.

[System]



Assistant: