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https://github.com/dogweather/repo-health-check

Analyze a project: How are the maintainers doing?
https://github.com/dogweather/repo-health-check

Last synced: 26 days ago
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Analyze a project: How are the maintainers doing?

Host: GitHub
URL: https://github.com/dogweather/repo-health-check
Owner: dogweather
License: apache-2.0
Created: 2015-03-18T20:52:00.000Z (over 9 years ago)
Default Branch: master
Last Pushed: 2024-06-07T19:00:31.000Z (6 months ago)
Last Synced: 2024-11-09T19:41:56.313Z (about 1 month ago)
Language: CoffeeScript
Homepage: https://repocheck.com
Size: 903 KB
Stars: 76
Watchers: 4
Forks: 3
Open Issues: 15
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

awesome-ospo - Repo Health Check - Analyze a project: How are the maintainers doing? (Project Quality)

README

# Repo Health Check

Analyze a project and its management

![screenshot](https://raw.githubusercontent.com/dogweather/repo-health-check/master/docs/screenshot-medium.jpg)

[Live app →](https://repocheck.com/)

A fully client-side GitHub/BitBucket repo analyzer. It finds out: Is a
project well managed? Does it _accept help_? How does it compare to other
options? And then: what should you do to take your repo from **in the weeds** to
**_super effective_**?

It performs the hard work entirely in the browser so that each user's own API
rate limits are in effect. This avoids [problems similar projects](https://github.com/hstove/issue_stats/issues/10#issuecomment-58444422) have had, and means faster and more varied results.

## Use Cases

* **A developer looking for a library** wants to compare management styles of a few alternatives.
* **A developer thinking about contributing** to a project wants to know if it's worth it.
* **A job candidate wants to know** how a prospective employer manages their projects.
* **A company** wants to see if all its projects are being managed similarly.

## Development Status

One metric is implemented (**effectiveness**) and I'm brainstorming about next steps:

* More metrics
* Advice for improving the issues found
* New visualizations, and better UX

## Automated Signals

Quantitative measurements which can determine _qualitative_ assessments.

* Num. of active branches
* merged
* un-merged
* Num. of stale branches
* merged
* un-merged
* Num. of open pull requests
* proportion open:closed pull requests
* aging of pull requests
* Num. of open issues
* proportion open:closed issues
* Num. of stars
* Num. of forks
* Num. of subscribers
* ratio of # of tags to # of tags in use

### Intermediate Metrics

By using the raw signals listed above, we can calculate useful metrics. These metrics, then, will be the pieces that can form a judgement for the big questions.

E.g.:
* How well do the maintainers keep up with the queue of incoming PR's?
* How quick do the maintainers respond to new issues and PR's?
* How does the activity level affect the other metrics?

### Other sources

* Code Climate score
* Travis CI passing

### See Also

* https://www.quora.com/If-a-GitHub-project-has-a-lot-of-forks-what-are-some-guidelines-for-choosing-the-right-one

### Useful Tech

* [Hello.js OAuth](http://adodson.com/hello.js/)

## Similar Projects

* https://repohealth.info / https://github.com/pelson/repohealth.info
* https://github.com/cfjedimaster/githubhealth
* https://github.com/hstove/issue_stats
* https://github.com/ryo-ma/github-profile-trophy