We’re all looking for jobs.

What it does

Analyzes the tone of a cover letter for qualities such as overall sentiment, confidence, and emotion. It highlights the stronger sentences and suggests areas for improvement.

How we built it

We used Loopback, Watson’s NLU and Tone Analysis APIs as well as Quill.js

Challenges we ran into

Other than the fact that we’re all new to Loopback and Watson, we found it challenging to think about what kind of feedback would be most helpful for someone using this app and how to best represent that feedback.

Accomplishments that we're proud of

We have successfully figured out how to integrate Watson APIs into our Loopback app. We worked harmoniously and productively together, complementing each other’s strengths.

What we learned

For many of us, this is our first hackathon, so we learned a lot about how to prioritize and divide up building out the main functionality of the app given the time constraint. We also all learned everything we now know about Loopback and the Bluemix platform over these past 3 days =)

What's next for Covfefe-Letter

-We’d like to implement a feature that allows you to upload a specific job post and have it analyze whether you are using enough keywords from the job description. -We’d also like to explore how we could use the Natural Language Classifier help make specific suggestions for the user’s tone, i.e. give a list of more confident words/phrases.

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