Have Alexa tell you how you've been doing based on the positivity/negativity of your recent tweets.
Switch branches/tags
Nothing to show
Clone or download
Type Name Latest commit message Commit time
Failed to load latest commit information.
speechAssets Added intent schema and sample utterances Nov 15, 2015
.gitignore Little bit of cleanup Apr 10, 2016
AlexaSkill.js Added code! Yay! Nov 15, 2015
LICENSE Initial commit Nov 15, 2015
README.md Updated README. Nov 15, 2015
index.js Little bit of cleanup Apr 10, 2016
package.json Initial commit; added package.json Nov 15, 2015



Have Alexa tell you how you've been doing based on the positivity/negativity of your recent tweets.

My favorite comment on the nature of mirrors and humans is that we don't just look at ourselves in them to ensure we look presentable; in some sense, we look at ourselves in mirrors just to make sure we're still there. Unfortunately, I don't remember who voiced that idea, but I'm happy to try and keep it alive. CheckTheMirror is an Alexa Voice Skill that performs a sentiment analysis on your most recent tweets and lets you know how you're doing--be thee positive as of late or negative.

So next time you're in a rush, throwing on your tie or combing snarls out of your hair, when you stop to look at yourself in the mirror for that brief but telling moment--that moment where, if but for the only time that day, you're sure that you exist--say aloud, "Alexa, ask the mirror how I've been lately" and listen for some insight into your recent Twitter history that you may not have even consciously recognized.


You'll need to set up a Twitter application to give the voice skill access to your tweets. Once completed, clone the repository and run npm install; this will download and install the twitter and sentiment-analysis dependencies. Create an AWS Lambda function and Alexa Voice Skill, and fill in the AWS app ID and Twitter keys in index.js. Zip together index.js, AlexaSkill.js, and node_modules so that all three are in the root of the zip, then upload it as the code to the AWS Lambda function.

I realize these installation directions are somewhat vague, but this is a project for HackRPI Fall 2015, so I'm not going for any completeness awards.

And let's face it, art is supposed to be vague, right? I say "art" because god knows this project has little to no practical value.