Your README Report Card

We've analyzed the README for Twangist/log_calls, and here's what we've found.

    Overview
    Headers
    Code Samples
    Text
    Images

C
Your README's Overall Grade

Your overall score is calculated as an average of your README's headers, code samples, text, and
image scores. Each section provides insights and suggestions for improving the quality of your
README relative to the 10,000 popular repositories we've analyzed.

These grades are not definitive. Rather, they're the result of machine learning, and are provided
on a "best effort" basis. We recognize that the model doesn't account for all the complexity and
nuance a README has. Ultimately, you should use your own judgement about what to include, remove,
and ignore. Inevitably, there will be results that don't make sense. tl;dr data science is hard.

Feel free to contact us @Algorithmia or by email if you feel something is particularly egregious.

Model Assumptions

    Popular repositories probably have a good, well-documented README
    Popular repositories have more stars than bad repositories
    Each programming language has unique characteristics

In general, we found a higher correlation between a README's quality and the specific
headers, and text used throughout. Conversely, we found a lower correlation between
the quality and the number of code samples, and the number of images in the README.

In order to correct this, we removed any repository that had zero images, or code snippets
from our model, because these are helpful, additive features.

Note: If the README you analyze falls outside of the top 10 langauges (i.e. Javascript,
Java, Ruby, Python, PHP, HTML, CSS, C++, C, or C#), we default to using a model trained
on all of the languages.

How was this made?

Learn more about our data science approach to analyzing GitHub README's, and find
the complete code sample in the Algorithmia Sample Apps repo here, which earned
a B grade.


D
Section Headers

Having clear section headers help users quickly find what they're looking for.
Our recommendations provide guidance on what sections you should consider adding,
changing, or removing. In many cases, section headers can come in multiple forms.
Such as Install, Installing, or Installation. In these situations, we simply pick
one, and recommend it. Feel free to pick your own flavor.

    Uh oh. Your README header score is 2 out of 10.

Consider Adding

Your README could be improved by adding these sections:
helping file contributers bug development author

Try Removing

Popular README's typically don't have these sections:
installations basic

C
Code Samples

It should go without saying that code samples are extremely helpful. Many
developers jump straight to code examples, rather than reading the
documentation. Here, we attempt to make recommendations relative to the
average number of code samples in the most popular repositories.

The average README has 8.33 code samples.

    Your README scored 4 out of 10 on code samples. Consider removing a few to improve your score.


B
README Text

The text of your README is important, because it explains what your README is about,
how it works, why you need it, and more. Your README should be readable, coherent, and clear.

Our model analyzes every word used throughout your README to suggest keywords commonly used
in popular README's. For instance, if we recommend that you include a word like "globals,"
perhaps you should include a sentence or two describing the role of globals in your project.

    Amazing! Your README text score is 7 out of 10.

Consider Adding

Popular README's tend to use more of these words:
query prefixes implement dependant send easiest

Try Removing

These words aren't typically found in popular README's:
coded profiled


D
README Images

Popular repositories on GitHub often have images or badges in their README's. The badges
indicate things like continious integration, build status, or package manager inclusion.
Other types of images, such as screenshots or GIFs, can also be useful in conveying
information about the output or how the code works.

The average README has 2.89 images.

    Yikes! Your README image score is 3 out of 10. Most README's have two or more images.

