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Zincr is a Github bot built with Probot to enforce approvals, specification and licensing checks
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A GitHub App built with Probot to scan pull requests for specification, licensing and approvals.

Galvanization or galvanizing is the process of applying a protective zinc coating to steel or iron, to prevent rusting. The most common method is hot-dip galvanizing, in which the parts are submerged in a bath of molten zinc.

The app will leave a comment on each pull request with instructions on how resolve the issue, and also provide a full list of checks performed in a status check - if any checks fails, it will block the merge.


Install on Github

Install via Github Apps out of the box, the bot will run pre-configured checks on all pull requests:

The checks will rerun on new PRs, PR updates and when PRs are reviewed. Details on each check is outlined further down.


You can modify the default behavior by adding a /.zappr.yml or /.github/zincr.yml file - each task has a configuration section which corresponds to its name, if the check is not specified in the config, it will not run.

Sample config:

  includeAuthor: true
  minimum: 2
  enabled: true

  enabled: true
    - MIT
    - ISC
    - MPL-2.0

  enabled: false

Available Checks


Checks if a minimum number of team members have approved a proposed change in a pull request. The checks counts the number of reviews approving the change and have the option to include the author in the final count of reviews - if the author is a member of the current organisation where the repository exists.

This check is somewhat stricter than standard GitHub reviews as it will dismiss all reviews by team members who have contributed to the pull request.

Example: User A submits a PR, User B has access to the branch and makes changes to this branch directly. Normally GitHub reviews will allow User B to approve the PR and thereby allow changes without review to enter the master branch. This check will dismiss any approvals by users who also have commits in the PR branch - except for changes made via the suggestion feature, as these are approved by the original author before inclusion.


Config options:

  // true by default, if the author is a member of the org it counts towards the total count of approvals, if the bot is running on a non-org repo, it will check if the author have write access to the repo. 
  includeAuthor: true
  // Number of people who must reviee and approved [default is 2]
  // If include author is enabled this will count as a positive review
  minimum: 2
  enabled: true


Checks the license of dependencies i npm, pip, sbt and gradle license files (uses License-Lookup - if a pull request includes new dependencies, this check will warn the maintainers to review the dependency, if the dependency licensing can be detected it will determine if the license is either compatible with the allowed or exclude licenses or the base license of the repository.

Config options:

  enabled: true
  // Either determine compliance based on a base license (Use SPDX identifier):
  baseLicense: MIT
  // ...Or use specific allow/exclude lists (Use SPDX identifiers)
    - MIT
    - ISC
    - MPL-2.0
    - AGPL-3.0

exclude and onlyAllow have overloads to use a pre-set list of licenses of a specific type instead of SPDX IDs, these are: publicdomain,permissive, weakcopyleft, strongcopyleft and networkcopyleft


Check to determine if the specification of a pull request follows specific style rules, it must have a minimum length, include a url, and include an issue ID, each individual check can be enabled/disabled

  enabled: true
      length: 8
      enabled: true
      length: 8
      enabled: true
    // Enforce that all PRs have a url  
    contains-url: false,
    // Enforce that all PRs have a github issues ID (#1234)
    contains-issue-number: true

Large Commits

Check to detect big changes made to a file in a single commit to warn of potential large changes which can have a higher degree of complexity and have a bigger risk of being an external code snippet pasted into the codebase and therefore need to be reviewed carefully for copyright and licensing issues.

  enabled: true
  maxLines: 100


Use either npm, VSCode or docker to run the bot locally


# Install dependencies
npm install

# Run typescript
npm run build

# Run the bot
npm start

VS Code

There are 2 Vs Code configurations included, a jest config to run all tests, and a task to run a local probot with a Vs Code attached debugger - open the VSCode debugger and choose "Launch Probot"


Using docker, you can launch a local smee connected instance of the bot, ensure that you change the docker-compose file config for App ID and smee url before running. also, the docker script expect there is a prod.pem file in the root of the project/

docker-compose up zincr


If you have suggestions for how Zincr could be improved, or want to report a bug, open an issue! We'd love all and any contributions.

For more, check out the Contributing Guide.


MIT © 2019 Zalando SE, Author: Per Ploug

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