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:

Insightfulness: Is the response creative, original or novel, including new perspectives or interpretations of existing information?
Score 1: The response is overly simplistic, lacking any originality or novelty.
Score 2: The ideas or perspectives within the response are commonplace, demonstrating a lack of originality or novelty.
Score 3: Some may perceive the response as original and novel, but others may find it ordinary or uninspiring.
Score 4: The response includes some innovative perspectives or ideas that require thoughtful consideration, yet they aren't particularly surprising.
Score 5: The response is infused with surprisingly creative perspectives or ideas that are challenging to conceive, showcasing significant originality and novelty.
Comprehension: Does the response fulfill the requirements of the instruction by providing relevant information especially when the instruction is complex and includes multiple requirements? This includes responding in accordance with the explicit and implicit purpose of given instruction.
Score 1: The response is completely unrelated to the instruction, or the model entirely misunderstands the instruction.
Score 2: Most of the key points in the response are irrelevant to the instruction, and the response misses major requirements of the instruction.
Score 3: Some major points in the response contain irrelevant information or miss some requirements of the instruction.
Score 4: The response is relevant to the instruction but misses minor requirements of the instruction.
Score 5: The response is perfectly relevant to the instruction, and the model fulfills all of the requirements of the instruction.
Completeness: Does the response provide a sufficient explanation? Comprehensiveness and thoroughness of the response should be considered, which depends on the breadth of topics covered and the level of detail provided within each topic.
Score 1: The response doesn't include any specifics or examples to support the statements made.
Score 2: The response does not provide sufficient details or supportive examples, requiring a major effort to make the response more complete.
Score 3: It is a decent response, but the breadth and depth of the response are rather limited. The details and examples used to substantiate the response may be insufficient.
Score 4: The response provides detailed explanations, but there is room for enhancement. The response could be further improved by including more details and supportive examples.
Score 5: The response fully provides comprehensive explanations. It delves deep into the topic, providing as much detail as possible, and it offers several examples to back up its points.
[Instruction]
Make a list of desirable Skills for software engineers to add to LinkedIn.

[Ground truth Answer]
Test-Driven Development
Object-Oriented Programming (OOP)
MVC
REST API
Technical Writing
Debugging

[Assistant's Response]
To enhance their professional visibility on LinkedIn, software engineers should consider adding a diverse range of skills that reflect both technical expertise and soft skills. Here’s a comprehensive list of desirable skills categorized for clarity:

### 1. **Programming Languages:**
   - Python
   - JavaScript
   - Java
   - C++
   - C#
   - Ruby
   - Go
   - Swift
   - Kotlin

### 2. **Web Development:**
   - HTML/CSS
   - React.js
   - Angular
   - Vue.js
   - Node.js
   - Django
   - Flask

### 3. **Mobile Development:**
   - iOS Development
   - Android Development
   - React Native
   - Flutter

### 4. **Software Development Practices:**
   - Agile Methodologies (Scrum, Kanban)
   - Test-Driven Development (TDD)
   - Continuous Integration/Continuous Deployment (CI/CD)
   - Version Control (Git)

### 5. **Cloud Computing:**
   - Amazon Web Services (AWS)
   - Microsoft Azure
   - Google Cloud Platform (GCP)
   - Docker
   - Kubernetes

### 6. **Databases:**
   - SQL (MySQL, PostgreSQL)
   - NoSQL (MongoDB, Cassandra)
   - Database Design

### 7. **DevOps:**
   - Jenkins
   - Terraform
   - Ansible
   - Puppet

### 8. **Data Science & Machine Learning:**
   - Data Analysis
   - Machine Learning
   - TensorFlow
   - PyTorch
   - R Programming

### 9. **Cybersecurity:**
   - Network Security
   - Ethical Hacking
   - Encryption

### 10. **Soft Skills:**
   - Problem Solving
   - Communication
   - Team Collaboration
   - Critical Thinking
   - Adaptability

### 11. **Project Management Tools:**
   - JIRA
   - Trello
   - Asana

### 12. **UI/UX Design:**
   - Figma
   - Adobe XD
   - User Experience Design

### 13. **Emerging Technologies:**
   - Blockchain
   - Internet of Things (IoT)
   - Artificial Intelligence (AI)
   - Augmented Reality (AR) / Virtual Reality (VR)

### Additional Tips:
- **Endorsements:** Seek endorsements from colleagues to validate your skills.
- **Contextualization:** Provide specific examples or projects where you applied these skills to give potential employers insight into your capabilities.

By strategically selecting and showcasing these skills on LinkedIn, software engineers can significantly enhance their professional profiles and increase their attractiveness to potential employers.

[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: